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Hello friends so today we are going to
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talk about the nanop particles
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nanomedicine and artificial
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intelligence and their role in advancing
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Health Care Systems so I hope you have
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already uh listened to the part one of
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this video where I have talked about the
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uh recent most noble prizes which have
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been uh awarded in this particular field
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of nanotechnology
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and artificial intelligence I had also
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mentioned about different kinds of
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nanomaterials available also uh how
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these nanom medicines are developed
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which kind of nanop platforms are used
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what is the difference between uh
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traditional and the Nano enabled
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Platforms in terms of uh drug delivery
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and uh also I had given a couple of
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examples about uh these nanom medicines
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uh so I covered almost uh everything
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about nanoparticles and nanom Medicine
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in the first part and how they are being
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utilized uh for
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uh the advancing the Health Care Systems
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uh in the first part so I'm hoping that
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you might have heard that by now if not
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you should go back and listen to that
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part uh first because in this part two
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I'm going to specifically focus on the
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artificial intelligence and its role uh
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in advancing the healthcare system so
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to uh quickly uh go to the artificial
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intelligence part you are you're already
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aware of the fact that uh AI is actually
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revolutionizing the healthcare by
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introducing Advanced Technologies and
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these Technologies actually uh are
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enhancing the Diagnostics treatments and
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patient care all at the same time uh
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simultaneously because most of the time
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these
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Diagnostics um or the treatment or the
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patient care uh systems go hand in hand
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in hand because you need to uh monitor
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everything uh simultaneously while you
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are taking care of a patient in
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particular for a specific uh
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disease so AI applications in Healthcare
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systems are obviously diverse starting
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from the um identifying the medical
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imaging and the uh processing of that
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data and finally leading to the uh
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personalized medicine for individual on
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the basis of all the uh data analysis
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and processing which is done using
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various data analytical tools and uh
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artificial
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intelligence uh uh simultaneously so Bas
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all this is done for the significant
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improvements in accuracy efficiency and
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the patient outcomes because you want
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your uh patient outcomes to be better so
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that uh at
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least you can
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reduce some Global burden of these
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diseases which are immense in number I
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have also talked about the global burden
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of the diseases in the earlier part of
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this video so you can uh check it out
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there that um uh how much Global burden
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these diseases are putting upon us and
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the pharmaceutical companies they are
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growing day by day the market is growing
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day by day lots of pharmaceutics are
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getting develops but still we need
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better uh Diagnostics and better far
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better pharmaceutics for the treatment
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of patients uh so as far as AI
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Healthcare market and numbers is
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concerned if you uh look at uh this data
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uh in
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2020 the global AI healthare Market was
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somewhere around $4.9 billion US in
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2021 a lot of startups came and almost
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2.5 billion US dollars were raised by
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these uh startups in 2024 this month
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Market is expected to increase by 45.2
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billion US and in 2026 it has to it is
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expected to increase by almost 45%
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making it to 150 billion US dollar in
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healthcare by
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2026 so you can understand that how
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important it is to study uh these two
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parallels uh together which means
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artificial intelligence and the uh and
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the Therapeutics u in this case we are
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talking about specifically about the
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nanotherapeutics or the nanom medicines
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and studying them together it becomes
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really important just by looking at the
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number you can understand that recent
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Nobel prizes have been awarded in um for
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the U for the artificial intelligence
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related work uh and also for the
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computational modeling of uh uh 3D
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structure of protein using the machine
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learning so more or less both have been
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awarded in the field of artificial
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intelligence or machine learning making
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it all the more
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important so if I just give you an
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example of an AI application in
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healthcare uh just uh let's say we if we
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talk about the liver cancer and how
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artificial intelligence is playing any
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role in liver cancer so starting from
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the uh virtual assistance which patient
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might might use in terms of of um
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identifying the starting from the uh
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doctors or the Path Labs or uh to talk
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to somebody about uh their symptoms
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these virtual assistance in the form of
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the UMC different kinds of mobile
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applications or the even chat gpds or
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chat boards these applications have been
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utilized um utilized uh
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variously utilized by uh different uh
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even different hospitals or different
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healthc Care Professionals nowadays so
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this is one example then second example
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uh is that the medical image Imaging
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diagnosis is being done um using these
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artificial intelligence related
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applications and uh these medical images
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U are initially collected segmented
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processed and then analyzed by uh by the
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um AI profession and then they develop
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certain AIDS or the or the
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tools diagnostic tools which are lated
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later utilized by the healthc Care
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Professionals also that is another uh
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another research field which is being
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utilized uh for uh these applications
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then they can also be used for the eduin
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therapy which means a follow-up therapy
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after a treatment is more uh more or
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less is done and then uh the follow-ups
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have to be taken care of so that can be
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taken care of by the artificial
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intelligence or so the RIS risk
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screening treatment response prediction
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and prognosis evaluation all that can be
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done computationally using artificial
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intelligence and then also uh in
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case uh better drugs with better uh
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efficacies better um targeting and uh
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better bio distribution and there are a
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lot of things which still needs to be
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improved so drug development and testing
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can also be done by utilizing a AI
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applications and also uh the
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postoperative rehabilation
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rehabilitation management once the
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patient is operated for a disease and
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then after that Rehabilitation is done
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so there can be different kinds of
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applications uh which are AI based which
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can be utilized by um a patient or a
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healthcare professional for the
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betterment of the patient
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outcomes so this is one example which I
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have given to you there are some other
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examples like for example if we talk
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about medical imaging so this can be
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used for the enhanced Diagnostics uh AI
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algorithms uh analyze Medical Data like
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x-rays MRIs and CT scans and uh they try
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to identify different kinds of
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abnormalities which are later uh used by
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the radiologist for diagnosing the um
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patient condition more effective ly and
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um at the earliest possible for
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example Google's deep mind uh has
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developed Ani system that can detect
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over 50 eye diseases from retinal scans
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with uh accuracy comparable to export
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opthalmologist so it can identify more
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than 50 diseases um all it all very um
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clearly specifically and probably better
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than an export uh another example can be
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in the form of the image segmentation
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where AI performs different kind of
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image segmentation uh and differentiate
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between healthy and the disease tissue
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so that a better planning for the
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disease treatment can be done the um an
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example has been uh given as the AI tool
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like unit segment which which basically
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segments tumor boundaries in brain MRIs
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providing crucial information for
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surgical planning so these are some of
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the
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examples which are of artificial
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intelligence in terms of health care but
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these are not limited uh as far as
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medical diagnosis is concerned AI
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basically is being used for uh this
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application uh in particular to improve
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the accuracy and speed of the disease
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diagnosis as we um always keep listening
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uh to this particular thing that um that
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early diagnosis can
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improve the chances of Sur sural of a
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patient or the patient outcome uh can be
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really uh really improved if a disease
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can be identified at an early stage
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specifically um like cancer
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disease so AI has been uh sort of uh
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helping uh people out in identifying or
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diagnosing the diseases uh using the
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different kinds of algorithm based on
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the different kinds of data uh which are
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available um uh available with the
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healthcare professionals and uh
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different
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algorithms uh have been used not only
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for the diagnosis but also for the
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prediction of the diseases and for the
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um identification of the diseases as
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well similarly AI is utilized in uh in
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mental health has been for the uh same
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use cases it can be used so because it
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can analyze data related to different uh
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mood patterns the behavioral data can be
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identified and then depending upon that
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data um identification analysis a
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treatment plan can be based on the same
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and uh other than that obviously there
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are different kinds of chat boards
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available where people can talk to these
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chat BS
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or uh the whatever the social stigma is
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related to these mental health issues
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can be avoided because in that case
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people are not much are not too bothered
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about
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um about uh with whom they are talking
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to they can very confidently talk to
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these chatbots and try to find out the
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solutions of their problems and uh
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sometimes probably this can work better
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than uh better than talking to somebody
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in particular in person um there is a
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possibility so that is also uh another
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example where people have been utilizing
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these applications of late another thing
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is uh AI can be utilized in personalized
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medicines because uh once you have the
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patient history and you have the uh
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genetic profiling of a patient uh
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depending upon the genetic profiling of
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the patient doctor identifies the
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specific disease or the disease markers
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and then on the basis of that uh he
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basically plans the um the treatment of
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the patient and so that his uh therapy
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can be optimized and finally uh the
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there there there can be minimal side
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effects so and a personalized medicine U
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can be planned for an individual and AI
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certainly uh AIDS in these treatment
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plans likewise for the drug Discovery I
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can be used because uh drug drug
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efficacy can be predicted easily by the
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by Ai and uh it can also help in
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identifying the potential t
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in new
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therapies so this application is
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also quite important uh in terms of the
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Healthcare System new drugs can be
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identified on the basis of the same
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likewise AI is utilized in Radiology as
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well because Radiology deals with a lot
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of scans so since it deals with a lot of
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scans so these scans can be um can be
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feed into the
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uh the system and the different AI
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algorithms can predict the uh disease or
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sometimes even which uh which um which
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particular um treatment plant might
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treatment plan might be better um over
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the other can also be planned U on the
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basis of these uh artificial
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intelligence related uh
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applications U surgery robotic surgeries
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you all of you might have heard by now
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uh can be uh done it is now possible in
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uh some specific particular
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hospitals uh likewise Nano robots have
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been utilized for delivering the drug uh
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to these specific target cells um that
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is also another artificial intelligence
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based uh uh based um
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example which is utilized in the
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healthare
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systems so artificial intelligence
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basically is revolutionizing this whole
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world of uh world uh by giving better
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treatment Plans by better uh diagnostic
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measure by giving better diagnostic
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measures by uh sort of giving the uh
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giving the aid to the already existing
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Health Care System uh likewise it can
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also uh be it can also be uh utilized
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for the um uh for the different kinds of
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for some other different kinds of uh
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applications also for example you can
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utilize it for the management of medical
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records uh robot assisted surgery I've
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already mentioned to you it can be also
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utilized to detect the fraud detection
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and then customer service based chatbots
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are already there which I just mentioned
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to you virtual Health assistants are
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there and then um accurate cancer
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diagnosis improved Healthcare access so
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there are different kinds of
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applications which are already aware so
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artificial intelligence is used to
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describe the machines that
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mimic the cognitive functions that
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humans associate with other humans human
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Minds there are a few uh spelling
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mistakes but anyhow so the basically
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artificial intelligence is utilized to
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describe those machines which more or
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less mimic the cognitive functions of
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the human mind and then they try to
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solve the problem by and they try to
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learn the problem and give the solution
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for them uh same so artificial
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intelligence and Nar nanotherapeutics go
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hand in
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hand and they have a potential to
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transform the Health Care
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system so one uh more example can be of
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the prediction of the drug
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potency algorithm can be utilized
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because uh they can analyze B data sets
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of molecular structures experimental
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results and clinical trials to predict
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the effectiveness of drug candidates uh
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accelerating drug Discovery and
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development so these uh these U kind of
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studies which utilize in silico drug
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screening Ino drug scanning and finally
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reaching to the nanoos discs for
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monitoring drug release doing an
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efficacy can also be um aided using
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artificial
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intelligence uh another example is that
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they can be utilized for the microscopic
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analysis where different kinds of images
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come from microscopes then uh different
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uh kind of patterns and features can be
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identified which are usually which might
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usually be missed by the human eye and
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then they can lead to the
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characterization and optimization of
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nanomaterials and the uh which can
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further be utilized by the
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nanotherapeutics uh this example I have
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already shared with all of you already
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personalized medicine which AI can
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analyze the patient data including its
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genetic information and medical history
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uh so that it can so that they can
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identify the personalized treatment plan
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for the targeted delivery of
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nanotherapeutics so nanotechnology
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basically is helping in the not only
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diagnosis but the treatment selection
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and the personalized medicine and
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obviously in the followup of the disease
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so this is a synergistic approach in
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which the um artificial intelligence
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andap itics have been helping each other
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for the better patient outcome one
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example very recent example is of uh
00:18:08
this uh particular uh kind which is of a
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smart bracelet as you might already know
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that epilepsy is the fourth most common
00:18:18
neurological disorder in world so um
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identifying the
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scissors uh on time or predicting the
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scissors Before Time is extremely
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important so this AI driven band which
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is a smart bracelet kind of band uh
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embraced to it is uh being uh utilized
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for now the detection of the possible
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convulsing scissors and this is a AI
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driven band which uses the algorithm to
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detect the possible convers convulsive
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scissors so such products have been
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coming up in the market uh now another
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example is of the this app which uses
00:19:00
the which basically identifies the
00:19:02
stroke uh it also uses the Deep learning
00:19:05
algorithms and it automatically detects
00:19:08
a stroke on CT Imaging as soon as you
00:19:10
feed in a CT image it will immediately
00:19:13
um tell you whether uh whether this
00:19:16
image is of a patient who has just had a
00:19:18
stroke or not or who had the uh I mean
00:19:21
even going before to the to discuss it
00:19:24
with the medical professional you
00:19:26
already know that um that uh the patient
00:19:30
already had a stroke this is another
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important uh application which is
00:19:36
already uh in the market
00:19:39
now one very important and interesting
00:19:42
example is of the vocal biomarkers
00:19:44
basically AI is able to help in
00:19:47
diagnosis through the sound of the voice
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of patients
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specifically uh for example in the
00:19:52
patients like of Alzheimer's and
00:19:54
Parkinson's disease where patient might
00:19:57
be having a little difficult in speaking
00:20:00
or um they their their speech is little
00:20:03
altered so these vocal biomarkers in the
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form of their altered speech uh can be
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utilized uh from the phone records to
00:20:13
analyze the risk of Alzheimer's or the
00:20:16
Parkinson's disease and these algorithms
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are developed to
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detect and in addition to that some
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algorithms have been detect to developed
00:20:25
to detect the covid-19 vaccine Co 19
00:20:29
virus um even by just scuffing into
00:20:31
their smartphone apps and um that could
00:20:36
detect the uh covid-19 virus
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so very nice and very uh Innovative kind
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of applications people have been
00:20:46
utilizing uh for various applications uh
00:20:51
which are utilizing artificial
00:20:53
intelligence uh algorithms for
00:20:56
identifying diagnosing treating
00:20:59
uh the patients uh and advancing the
00:21:02
Health Care
00:21:03
Systems uh another example is of the
00:21:06
detecting arthas arthia you are you
00:21:09
might know that it is a it is also known
00:21:11
as cardic arithma and it is basically an
00:21:14
irregular heartbeat that can cause your
00:21:16
heart to beat either too fast or too
00:21:18
slow or with an irregular Rhythm and it
00:21:22
hence increases the risk of stroke or
00:21:24
heart failure and other heart related
00:21:26
complications so this AI application
00:21:29
which is uh medical grade ECG recordered
00:21:32
that is electrocardiograph recorded it
00:21:34
is already FD approved over the counter
00:21:37
use scale available for the over the
00:21:39
counter use it creates analyzes and
00:21:42
displays electrocardiograph data and can
00:21:45
provide information for identifying
00:21:47
cardiac
00:21:49
arhas so you can just have it in the
00:21:51
form of the arist band and uh get your
00:21:54
electrocardiogram data and identify the
00:21:57
um the uh cardiac Arias on your own as
00:22:01
well uh this is this is also in the
00:22:05
market now another application is of the
00:22:07
Nano
00:22:08
Qs which is quantity structure Rel
00:22:11
activity relationship models these
00:22:14
models are when combined with AI can
00:22:16
assess the toxicological effects of
00:22:19
nanoparticles uh so they by uh by
00:22:22
predicting toxicity AI can help uh in
00:22:26
designing safer nanom medicines before
00:22:28
even clinical trials begin so a model
00:22:31
called Nano qsr it helps in uh
00:22:35
evaluating potential toxicities and
00:22:37
safety concerns for different nanom
00:22:39
materials and it aids in regulatory
00:22:41
approval so it collects the data uh
00:22:44
train the algorithm and then finally uh
00:22:47
is utilized for evaluating the
00:22:50
cytotoxicity uh in uh so all these uh
00:22:55
applications which I have talked about
00:22:58
uh uh just now in addition to that there
00:23:02
are some other applications also which
00:23:04
can be utilized by these AI powered Nano
00:23:08
AI powered um
00:23:11
nanotherapeutic uh Nan sorry I mean they
00:23:16
are sort of AI powered n
00:23:18
nanotherapeutics Only which are being
00:23:20
utilized uh in the Healthcare
00:23:22
systems for
00:23:25
example they can be utilized for the
00:23:27
molecular designing so AI algorithms can
00:23:30
assist in the rational design of
00:23:32
nanoparticles and optimal
00:23:33
characteristics for drug delivery you
00:23:35
can identify which kind of nanoparticle
00:23:37
do you need and what should be their
00:23:39
properties and then finally you can
00:23:41
design them for a specific kind of drug
00:23:44
delivery uh system likewise you can have
00:23:47
the predictive modeling predictive
00:23:49
modeling uh would have the AI powered
00:23:52
simulations which can predict the
00:23:53
behavior and performance of
00:23:55
nanotherapeutics in complex biological
00:23:57
systems
00:23:59
then High throughput scen screening can
00:24:01
be used uh which uh AI enabled platforms
00:24:05
can accelerate the screening and
00:24:06
evaluation of large libraries of
00:24:10
nanomaterials uh these these can be
00:24:13
utilized for developing uh some uh new
00:24:17
kind of material and also data driven
00:24:20
optimization can be done using uh
00:24:23
machine learning learning algorithms
00:24:25
because a vast data sets set uh is uh
00:24:28
large was large data sets are available
00:24:31
for the design and development of
00:24:33
nanotherapeutics so artificial
00:24:35
intelligence can Aid into all these
00:24:38
kinds of applications similarly if you
00:24:41
talk about the convergent roles uh the
00:24:44
roles of AI and nanotherapeutics so uh
00:24:48
not one example is given here but then
00:24:51
it can be it can be for uh a lot number
00:24:53
of
00:24:55
diseases cancer diagnosis and treat
00:24:57
treatment
00:24:59
AI powered image analysis can assist in
00:25:01
early cancer Diagnostics or detection uh
00:25:05
and then by nanotherapeutics can deliver
00:25:07
chemotherapy drugs directly to tumor
00:25:09
cells improving treatment efficacy and
00:25:12
reducing side effects so if you know uh
00:25:15
that a patient has cancer and he's
00:25:17
diagnosed early he or she's diagnosed
00:25:19
early then nanotherapeutics can be
00:25:21
delivered on time with better efficacy
00:25:23
and better uh specificity so that uh
00:25:27
side effects can be reduced and the
00:25:29
patient outcomes can be better likewise
00:25:31
neurological disorders can be um
00:25:33
identified early or diagnosed early
00:25:36
depending upon the U AI based
00:25:38
applications and finally timely
00:25:40
interventions can be done in terms of
00:25:42
the uh in terms of the um treatment
00:25:48
plans uh also uh one example had
00:25:51
recently been of covid-19 where
00:25:53
nanotherapeutics have been used for the
00:25:57
rapid diagnostic
00:25:58
tests where uh if we talk about even the
00:26:02
vaccination which were developed by
00:26:04
fiser and Monna so those uh vaccines
00:26:07
were uh mRNA vaccines and they they had
00:26:11
lipid lipid nanoparticles as their shell
00:26:16
uh they were encapsulated in Li lipid
00:26:18
nanoparticles so that they can they can
00:26:21
go inside the cell
00:26:24
and uh would not uh would not be caught
00:26:27
by the
00:26:28
uh mRNA degrading enzymes and also since
00:26:32
they are negatively charged and the cell
00:26:33
membrane is also uh negatively charged
00:26:37
so lipid nanop particles were needed as
00:26:40
a core so that they can go inside the
00:26:42
cell uh easily so the these were the
00:26:46
recent examples and
00:26:49
vaccination have been for covid-19
00:26:52
vaccination uh these have already been
00:26:54
used similarly in Antics for advancing
00:26:57
these system systems can be utilized for
00:26:59
better diagnosis of these infectious
00:27:01
diseases and for delivering antiviral or
00:27:04
anti bacterial
00:27:07
drugs anti antibacterial agents it can
00:27:09
be
00:27:12
utilized but uh in addition to uh these
00:27:17
there are uh a lot of
00:27:19
challenges uh in using Ai and
00:27:22
nanotherapeutics Inter
00:27:24
integration uh the most important
00:27:26
challenges of the data privacy in
00:27:28
security because the AI requires large
00:27:31
data sets and obviously that data set
00:27:35
comes from the patient history uh and
00:27:38
the patient data because patient gives
00:27:41
its data in the form of demography
00:27:44
biochemical data and then clinical data
00:27:48
um there are lots of data which is
00:27:50
collected so that um the the privacy and
00:27:54
security of that data is one of the
00:27:56
maing major concern that how to go about
00:27:59
it and then there are second concern is
00:28:02
of the regulatory hurdles because taking
00:28:05
approval um of utilizing nanooptics and
00:28:08
AI driven Healthcare technology is quite
00:28:10
complex and time consuming because it is
00:28:12
a very recent field so still a lot of
00:28:16
hurdles are coming up in uh in U taking
00:28:21
the um approval or maybe even the even
00:28:25
the formulating the approval policy es
00:28:28
so that is another important challenge
00:28:31
uh in terms of using these integration
00:28:37
of AI and Antics then there is third
00:28:40
challenge which is transparency and
00:28:42
explainability because AI algorithms can
00:28:44
be complex and difficult to understand
00:28:47
so obviously they raise the concern
00:28:48
about transparency and explainability of
00:28:50
decisions that how exactly the the
00:28:53
machine is taking a decision whether it
00:28:55
is correct or not how corre how much
00:28:58
percentage of it is correct what is the
00:29:01
Precision how much is the Precision how
00:29:03
much is the accuracy so all these
00:29:05
concerns are obviously there and then
00:29:08
last but not the least are the ethical
00:29:10
considerations because AI which is used
00:29:14
in healthcare it uses it raises these
00:29:17
concern as well
00:29:19
because uh they are related to the
00:29:22
buyers or the fairness or the potential
00:29:24
of its
00:29:26
misuse uh so um these ethical
00:29:29
considerations are also uh there but but
00:29:34
uh but we assume that uh sooner or later
00:29:38
since these Technologies are helping the
00:29:40
humankind as a whole and uh are really
00:29:45
needed for the betterment of patient
00:29:46
outcomes so they they will have these uh
00:29:50
challenges would be overcome by the uh
00:29:54
by the healthcare uh system
00:29:56
professionals or people who are working
00:29:58
in these fields so the future of nanom
00:30:01
medicine and Health Care is a
00:30:04
combination of all these that you would
00:30:06
need AI or ml guided formulations and
00:30:10
they will be developed using different
00:30:13
drug Discovery processes and the uh
00:30:17
different kinds of
00:30:18
methods uh which are there already being
00:30:22
utilized by the not only by the research
00:30:25
scientist as in the own personal Labs
00:30:29
but by pharmaceutical Industries also as
00:30:31
a whole and then the standards and
00:30:34
protocols for Purity and
00:30:37
reproducibility uh would be would be
00:30:39
made uh so that things can be reproduced
00:30:43
easily if anybody wants to and then
00:30:46
there would be uh good manufacturing PR
00:30:49
practices there should be good
00:30:50
manufacturing practices for scalability
00:30:53
because usually when they're made in lab
00:30:54
they they're made in very small
00:30:57
quantities but later they need to be
00:30:59
scaled
00:31:00
up so so that these can further be
00:31:03
utilized by tackling with the infe
00:31:06
diseases like covid-19 or The Chronic
00:31:09
lethal conditions like cancer so this is
00:31:12
what is the future of narom medicine
00:31:14
going to be that um artificial
00:31:17
intelligence and nerom medicine should
00:31:19
go hand in hand and they should be
00:31:21
utilized for the uh for the benefit of
00:31:25
the patients as a whole so that more and
00:31:28
more people get benefited uh we uh we
00:31:32
are able to save a more number of lives
00:31:35
so that because we should be able to
00:31:38
diagnose early we should be able to
00:31:40
treat better and then also another
00:31:43
another concern can be of cost so we
00:31:45
need to take care of the cost as well it
00:31:48
has to be uh minimal uh so that
00:31:51
everybody can afford it so all these uh
00:31:54
things need to be taken care of so I
00:31:56
hope in due course of time uh the
00:32:01
situation will get better and better and
00:32:04
nanom medicine and artificial
00:32:05
intelligence will uh certainly provide
00:32:09
uh hope to the uh hope to the patients
00:32:12
and uh their
00:32:15
caregivers thank you
