List of Medical specialities under threat by AI-2034.
Summary
TLDRDr. Dapu discusses the impact of artificial intelligence (AI) on various medical specialties, predicting workforce reduction due to AI's efficiency. He highlights AI's current and potential roles in radiology, pathology, dermatology, ophthalmology, cardiology, and anesthesiology, emphasizing AI's ability to handle routine tasks, allowing specialists to focus on complex cases. However, AI's limitations in complex decision-making, patient care, and interventions are also noted, with the overall message that AI will augment, not replace, medical professionals.
Takeaways
- 🧠 Artificial Intelligence (AI) is predicted to impact various medical specialties by increasing efficiency, but not replacing human professionals entirely.
- 🏥 AI is expected to cause a workforce reduction in medical fields, not by completely replacing professionals, but by decreasing the number of people needed to perform certain tasks.
- 📈 There is a current presence of AI in specialties such as radiology, pathology, dermatology, ophthalmology, cardiology, anesthesiology, and general medicine with software like Google's DeepMind and IBM Watson.
- 🛠 The efficiency of AI can lead to a significant reduction in the number of professionals required for routine tasks, allowing them to focus on more complex cases.
- 👨⚕️ In radiology, AI can process medical images faster and without fatigue, potentially reducing the number of radiologists needed for image analysis.
- 🔬 Pathologists may see a workforce reduction as AI can analyze tissue samples for diseases, reducing the need for human interpretation in certain cases.
- 🧑🔬 Dermatologists could benefit from AI in diagnosing skin conditions, allowing them to focus more on cosmetic procedures and patient counseling.
- 👁️ Ophthalmologists may utilize AI for retinal image analysis, early detection of conditions like diabetic retinopathy, and personalized treatment plans.
- 💓 Cardiologists might see AI assist in ECG interpretation, predictive analytics for heart conditions, and remote monitoring, but AI won't replace intervention procedures.
- 💉 Anesthesiologists could use AI for patient monitoring and pain management, potentially reducing the number of professionals needed for routine assessments.
- 🏘️ General medicine may see AI used for patient symptom analysis, suggesting lab tests, and forming reports for physicians to review, increasing the number of patients that can be seen in less time.
- 🚫 AI has limitations and cannot replace certain aspects of medical practice, such as complex case interpretations, interdisciplinary consultations, research, training, and building patient relationships.
Q & A
What is Dr. Dapu's primary concern regarding the impact of AI on medical specialties?
-Dr. Dapu's primary concern is that AI will not replace medical professionals but will decrease the workforce required to run various medical departments due to its efficiency.
Which medical specialties does Dr. Dapu believe will be most affected by AI?
-Dr. Dapu believes that specialties such as radiology, pathology, dermatology, ophthalmology, cardiology, anesthesiology, and general medicine will be significantly impacted by AI.
What are some examples of AI software already existing in the medical field?
-Examples of existing AI software include Google's Deep Mind in radiology, Path AI in pathology, Derm Tech in dermatology, and IBM Watson in various specialties.
How does Dr. Dapu envision the growth of AI in the medical field?
-Dr. Dapu envisions an exponential growth in the number of AI software and their capabilities, which will lead to a significant impact on medical specialties.
What is the potential impact of AI on the workload of radiologists?
-AI can process medical images faster and without fatigue, potentially reducing the number of radiologists needed to analyze images by up to 50%.
How can AI assist pathologists in their work?
-AI can analyze tissue samples for the presence of cancerous cells, potentially reducing the workload of pathologists and allowing them to focus on more complex cases.
What role can AI play in dermatology?
-AI can assist in diagnosing skin diseases by analyzing images, allowing dermatologists to focus more on cosmetic procedures and complex cases.
What are some specific tasks AI can perform in ophthalmology?
-In ophthalmology, AI can assist with retinal image analysis, early detection of conditions like diabetic retinopathy and glaucoma, and even monitoring and surgical assistance.
How might AI impact the role of cardiologists?
-AI can perform tasks such as ECG interpretation, predictive analytics for cardiac events, and remote monitoring, potentially reducing the number of cardiologists needed for routine diagnostics and monitoring.
What is the potential impact of AI on anesthesiology?
-AI could simplify patient monitoring, preoperative assessment, and pain management, potentially allowing fewer anesthesiologists to manage more cases and focus on complex case management.
What are some tasks that AI cannot perform in medical specialties?
-AI cannot perform complex case interpretations, interdisciplinary consultations, research and training, patient counseling, surgical procedures, decision-making in emergencies, and building relationships with patients.
Outlines
🧠 AI in Medical Specialties: Workforce Reduction
Dr. Dapu discusses the impact of artificial intelligence (AI) on various medical specialties, predicting that AI will not replace professionals but will lead to a workforce reduction due to increased efficiency. AI applications in radiology, pathology, dermatology, and other fields are highlighted, with examples of existing AI software like Google's DeepMind, IBM Watson, and others. The potential for exponential growth in AI capabilities is emphasized, suggesting a significant future impact on the medical workforce.
🔬 AI Applications in Medical Imaging and Analysis
This section delves into the specific applications of AI in medical imaging and diagnostics, particularly in radiology and pathology. AI's ability to process images faster and without fatigue is contrasted with the limitations of human radiologists and pathologists. The script outlines how AI can assist in reducing the workload and improving efficiency, leading to a potential decrease in the number of professionals required for routine tasks. The role of AI in dermatology, ophthalmology, and cardiology is also explored, with a focus on its current capabilities and future potential.
🚫 AI's Limitations and the Inevitability of Technological Advancement
Dr. Dapu acknowledges the limitations of AI, such as its inability to perform complex case interpretations, interdisciplinary consultations, and certain medical procedures. He emphasizes that while AI cannot replace the holistic care and relationship building in medicine, it can make processes more efficient and potentially lead to workforce reduction. The script concludes with the acceptance of AI's role in the evolution of medicine, suggesting that its development is unstoppable and will continue to shape the medical field, bringing both benefits and challenges.
Mindmap
Keywords
💡Artificial Intelligence (AI)
💡Neuroanesthesiology
💡Workforce Reduction
💡Radiology
💡Pathology
💡Dermatology
💡Opthalmology
💡Cardiology
💡Anesthesiology
💡General Medicine
💡Diagnostic Skills
Highlights
Dr. Dapu discusses the impact of AI on medical specialties and predicts workforce reduction due to AI efficiency.
AI is not expected to replace medical professionals but to decrease the workforce required in departments.
Examples of existing AI software in radiology, pathology, dermatology, and other specialties are provided.
AI's potential for exponential growth in capabilities and the number of AI softwares is highlighted.
In radiology, AI can process medical images faster than radiologists and reduce fatigue.
AI might lead to a 50% reduction in the number of radiologists needed for regular image interpretations.
In pathology, AI can analyze tissue samples for cancerous cells without fatigue, potentially reducing the workforce.
Dermatology can benefit from AI in diagnosing skin lesions and allowing dermatologists to focus on cosmetic procedures.
AI's role in ophthalmology includes retinal image analysis, screening, early detection, and monitoring.
Cardiology may see AI advancements in ECG interpretation, predictive analytics, and remote monitoring.
Anesthesiology could benefit from AI in patient monitoring, pain management, and training simulations.
General medicine may utilize AI for accurate diagnosis, lab test suggestions, and improving physician efficiency.
AI cannot replace certain aspects of medical practice such as complex case interpretation and patient relationships.
The potential for AI to make medical processes more efficient and error-free is emphasized.
A hypothetical scenario of a hospital reducing its doctor workforce by incorporating AI is presented.
Dr. Dapu concludes by stating that AI will make jobs easier but also poses a threat of workforce reduction.
Transcripts
hello this is Dr dapu I'm a senior
consultant in the field of
neuroanesthesiology so today I would
like to cover
the impact of artificial intelligence
that is AI on different medical
specialities and it is going to affect
and it is going it's not going to
replace you but it is going to decrease
the workforce that is my opinion and
when it is for example X number of
people are required to run a particular
Department then it is not going to repl
all X number of people but some
percentage of people would be replaced
because of the efficiency and you know
uh it will help you actually in working
right so you might not require the same
number of people to run that is called
Workforce reduction so that can happen
with AI is what is my prediction is so
if it is happening then in what
specialities it can happen see radiology
and pathology is what everybody knows I
will go through that and then apart from
that there are many other specialities
also which are going to get involved
I'll tell you about those things also
so then uh coming to the uh what are the
AA softwares already existing first you
try to understand so these are the a
softwares already there okay in
Radiology there is Google's Deep Mind
IBM Watson AI do and pathology there is
path AI page AI in Derm Tech in
dermatology there is Derm Tech IBM
Watson first DM in optology there is
Google's Deep Mind Octor as idx drr in
cardiology there is Ali Course cardia
Mobile zebra medical vision Electronics
AI in anesthesiology there studies is
Art and arteries and smart thoughts and
in general factors that is like general
medicine there is babyon health and om
so these many softwares are already
existing okay and then what I'm
envisioning is there won't be a linear
growth in this there will be exponential
growth in the number of softwares and
what they can actually do so that's
because that's how uh artificial
intelligence works so when the number of
softwares and all these things are
increasing there will be an impact on
speciality so let us start with
Dermatology okay so for example
Dermatology sorry Radiology let us start
with Radiology for example radiologist
is actually analyzing a medical image
and then can AI do it s AI can also do
with Pat recognition but not to the
level of radiologist at present but in
future it might do and the disadvantage
the Radiologists have is they get
fatigued heavy workload they cannot deal
so AI can actually process the images
faster and it doesn't get red okay so
what happens is for example uh as I set
of for example in a center there are 10
Radiologists they're analyzing for
example with 100 images and then by
using AI 50% reduction might happen and
then five ideologists can actually run
the show okay so all the complex cases
where you need to actually interact with
the surgeons interact with the
clinicians and do so those kind of stuff
maybe radiolog will do where regular
interpretations are there like XR and CD
scans and Mr to get the actual image e
can do it and radiologist can verify and
approve it so obviously it is more like
you know 50% of people can actually
manage the Radiology if the AI evolves
to a Next Level the same way uh it will
apply to a pathology also pathologist
can analyze the tissue samples and
diagnosed diseases the same sample you
put in AI it will also start analyzing
based on the cancerous cells how many
are there and everything it will start
analyzing so human interpretation can
have some kind of a fatigue and you know
all those factors AI will not have right
AI will never get Petty it'll keep doing
so in that way pathologist also can have
some kind of a uh Workforce reduction
when AI is fullblown okay so that is
about these two these two many people
know let us go other
specialities
okay so about Dermatology so Dermatology
if you uh take dermatologist usually
inspect skin lesions and then they
diagnose disease and give some ointments
and some are into cosmetic there's a
different sector cosmetic obviously a
cannot do so this particular part of
looking at the skin disease and
analyzing is what AI can actually do so
a algorithms are already there names I
already explained the Derm Tech and all
that so they are actually trying to if
you upload an image it will give you
some kind of a diagnosis whether it's is
right or wrong maybe dmist can approve
so again the workforce reduction can
happen even here so that dermatologist
can focus mostly on the Cosmetic
procedures and all that and then AI will
actually be doing the uh boring stuff so
that is about the
Dermatology and then dermatologist if
they have some confusion then AI can
actually maybe help them in going
through the wi database of all the
images and it can actually help them in
actually getting a better results also
in a faster way and T Dermatology also
can be done with the help of these
platforms
okay so this is this image I created in
Ai and something like this uh is going
to come up in future so you can actually
feed the skin disease in the uh AI
algorithm and it will actually analyze
it and give you a result you can you
just have to approve and then see if
this is the way the dermatologists are
operating then they can work on more dis
more diseases more tadi T Dermatology
also they can do and so they can
actually efficiently manage this
department so with lesser people also
they might be able to
manage so at present for example a
clinic is having eight dermatologist and
they're seeing 25 patients a day so AI
with diagnostic skills might and
decrease in the consulation time maybe
they can manage with four people in
future and then uh next speciality is
Opthalmology so optology retinal image
if you upload it analyze it will tell
you diabetic retinopathy grading and
gloma and there is Google's Deep Mind
which is there for diabetic retinopathy
and then
U also you know M screenings and all
these things also can be done with the
help of AI and Opthalmology GL Glo
detection monitoring also is coming up
now with a capabilities it will be able
to do that and also personalized
treatment plans can be done patient
education also can be done with a so
Opthalmology also might get ected with
the help of a in the same way okay so
now understood optology so retinal image
analysis screening and early detection
GL monitoring and surgical assistance
also can be done with the help of AI
this is by by all this overall impact
would be reduction in the Staffing
requirement few opthamologists are
needed to for a routine task so so that
the Opthomologist can focus more on the
complex cases surgeries and personalized
care okay better outcome will be there
we're not talking about outome we're
talking about the staff
reduction so threat is there is what I'm
telling Cardiology also can get affected
you can see ECG interpretation can
easily be done by feature image analysis
based on Echo can be done if technician
does Echo then interpretation can be
done by a Predictive Analytics it can
use and can actually predict who's going
to get cardiac who's going to get EMAs
and all that okay remote monitoring can
be done so a can assist in all these
things but can't do interventions right
interventions cardiologist would be done
so all the boring stuff AI would do and
again same problem can happen with
Cardiology also overall impact is the
same so overall impact will be fewer
cardiologists are needed to run the
Diagnostics Diagnostics and monitoring
and uh the number of cardi needed for
rtin task will decrease and complex
stuff and electrophysiology and putting
stands and all those things they would
be
doing okay and then the next uh would be
anes AIA in anesthesia mainly the if AI
comes up then patient monitoring becomes
easy and PR assessment also might get
easier and then pain management scales
and everything would become more easier
you can actually develop an AI which can
talk to the patient understand the uh
patient pain situation and then can
recommend medicines to the nurses in
that level actually in future it is
going to come nobody can stop
it and even trainings and simulations
would happen in a so overall would be
fewer
anesthesiologist can actually run the
[Music]
show anesthesiologist can actually focus
more on the complex case
management okay and general medicine so
in general medicine AI is usely going to
come so patients only might enter their
uh you know symptoms and everything into
the AI based uh software are already
existing which I I told the names of
them in the beginning of the video now
so then it might give a very accurate
diagnosis and if it is not giving then
it will be approved by a general
physician once the process is done maybe
a system can develop the patient will
enter that this thing and a will suggest
lab test and then lab test will be
analyzed by and forms a report the
report will be finally seen by The
Physician so that he can actually see
more patients in lesser time that is
what we're talking about I'm not telling
repl clinicians it is going to improve
decrease it is going to improve the
quality but it is going to decrease the
workforce that is what I'm thinking okay
so the these many specialities can get
affected because of the AI for example
this is a hospital then new hospital
current number of doctors are 76 10
radiologist 5 pathologist like some 76
doctors are there and if you incorporate
AI then uh what can happen is that
potential deduction in the doctors would
be 39 and 37 doctors would be remaining
this is how I think in future it might
happen like this might
happen so what a cannot do also we
should know see
the you're telling a will replace
doctors no a can't replace because a
cannot do so many things in ideology
complex case interpretation in pathology
uh the interdisciplinary consultations
research and training and dermatology
patient counseling and surgical
procedures and Opthalmology surgical
interventions in cardiology the
intervention procedures placing stuns
electrophysiology and in anesthesiology
the decision making the emergency
response and all that and crisis
management in general practice the
holistic care chronic disease management
and building relationships with the
patient it cannot do so there are so
many things it cannot do but at the same
time it can do something things can make
the uh process efficient it can actually
make the process uh you know error free
and it will whenever system becomes
efficient by technology that system
there was Workforce reduction the
history that is what I'm trying to tell
okay so overall impact is that I hope
you understood what I'm trying to tell
and uh so what is the solution for this
solution is nothing this is the
evolution and we are developing it and
uh there is no way anybody can stop it
so it is going to go in this Direction
let us see how it goes okay thank you
very much and
uh uh hope more and more a is going to
build up and make our jobs easier at the
same time the threat of workfor
reduction also is there let's see how it
goes thank you
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