Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again❰KINDLE❯ ❄ Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again Author Eric Topol – Bluevapours.co.uk One of America s top doctors reveals how AI will empower physicians and revolutionize patient care One of America s top doctors How Artificial MOBI õ reveals how AI will empower physicians and revolutionize patient care.

Is a well known author, some How Artificial MOBI õ of his books are a fascination for readers like in the Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again book, this is one of the most wanted Eric Topol author readers around the world.

Deep Medicine: How Artificial Intelligence Can Make
  • Kindle Edition
  • 400 pages
  • Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
  • Eric Topol
  • 17 September 2019

10 thoughts on “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

  1. Manzoor Elahi says:

    Critics hailed Big Data A Revolution That Will Transform How We Live, Work, and Think as a vision of future for big data But a lot of it turned out to be hype I see the same hubris in health care AI Take IBM Watson for example, IBM Watson still hasn t delivered much in health care We have seen the mess created by move fast and break things philosophy The way I see it, Deep medicine might be the move fast and break things in health care.Certainl Critics hailed Big Data A Revolution That Will Transform How We Live, Work, and Think as a vision of future for big data But a lot of it turned out to be hype I see the same hubris in health care AI Take IBM Watson for example, IBM Watson still hasn t delivered much in health care We have seen the mess created by move fast and break things philosophy The way I see it, Deep medicine might be the move fast and break things in health care.Certainly Artificial Intelligence will provide a helping hand in health care Take diabetic retinopathy, the number one global cause of vision loss If all the recommended screening of people with diabetes was performed, there would be well over 30 million retinal images per year that would need to be evaluated Clearly, this sounds like a job for deep learning.I was mesmerized when I read this line with the Aipoly app, a senior with significant visual impairment can simply point to an object with a smartphone and AI will quickly kick in with a voice response identification But on second thought I am not that impressed because it s not a cure it s just if all you have is a hammer, everything looks like a nail most of the anecdotes mentioned in this book are based on mobile applications, because most of the software engineers see the smartphone as the sole solution to every problem Since most startups are aiming to use smartphones as a diagnostic tool, it might result in overdiagnosis Artificial intelligence cannot replace actual science, it can help speed things up, it is a complimentary tool but it can never be a replacement for actual science.It reminded me of an anecdote told of the great American inventor Thomas Edison A practical man with little formal education, Edison nevertheless understood the value of education but also never missed a chance to show how a clever person could often work around a technical deficiency For example, after hiring a young mathematician Edison assigned him the task of determining the volume of a new lightbulb, a bulb designed with an undulating shape The mathematician carefully reduced the shape to a complicated equation and then laboriously, over a period of hours, integrated the equation over three dimensions to get the volume enclosed Then, he proudly showed the result to Edison.Edison congratulated the man on being a fine mathematician, as his computed answer agreed quite well with Edison s own value, which he had arrived at in less than 30 seconds When the astonished mathematician asked how Edison had done that, the inventor without saying a word simply filled the bulb with water and then poured the water out of the bulb into a glass beaker with volume levels marked on the side.Edison had made his point math is great, but use it as a tool and not as a crutch Same with artificial intelligence we should definitely use it as a tool but not as a crutch A gold mine is only as good as the man digging Artificial intelligence depends on good unbiased data Like facial recognition software that detects only white faces because the data it was trained on did not contain black faces, Deep medicine might inflate bias that already exists in the health care And finally like all things pertained with the information age there is the issue of privacy

  2. Isil Arican says:

    As an MD who now works on Healthcare IT field, I should start by telling that I am a big fan of Eric Topol and admire his vision in many ways I read his previous books, follow him on twitter and watched him live multiple times in various events When I was a TED translator, I translated couple of his TED talks to Turkish and he even acknowledged it in a signed book when I met him So I started to read this with a huge positive bias obviously.I liked the book overall He is giving a nice summ As an MD who now works on Healthcare IT field, I should start by telling that I am a big fan of Eric Topol and admire his vision in many ways I read his previous books, follow him on twitter and watched him live multiple times in various events When I was a TED translator, I translated couple of his TED talks to Turkish and he even acknowledged it in a signed book when I met him So I started to read this with a huge positive bias obviously.I liked the book overall He is giving a nice summary of the current issues in healthcare, the current status of AI, the update on the AI research related to healthcare, its various use in different areas, and finally provides a summary of where it might take us.Things disappointed me was to see the same cliche reasoning around the EMRs Yes, physician burn out is a big problem, and we should be worrying about it, and should try to find solutions to remediate it But like many others Topol puts all the blame to EMRs, and repeats the same mantra of how EMRs are the cause of all burnout and how they are designed for billing not clinical care Now as a person who works in this field I can attest that the latter is not true, at least not any The billing focused EMR is a thing of the past like 20 years or so, and those days are long past but it is an easy target so everyone use the same mantra rather than acknowledging the complex issues around healthcare, its finance, lack of appropriate and wide coverage primary preventive care, the policies, rules, regulations and finally IT The first claim EMRs being the cause of all burnout is also dubious in my opinion I am sure they do have an impact and definitely it is a factor that impacts patient provider interaction However, there are other causes like regulations, the monetary healthcare system, fee for service and faulty incentives As an anecdote, in my first EMR implementation job in the US, I was shocked to find out that the private practice I was working with was scheduling doctors so they see two patients at the same 15 min interval When they were doing this they were on paper, and had no EMR at all I could not even wrap my brain around how a doctor can see two patients in the same 15 minutes and advised against it So no, it was not the EMRs who disconnected the patients from doctors, it was the healthcare system itself And please do not tell me that providers were able to prep and chart properly for those patients they saw on average of 7.5 minutes each when they were on paper They weren t and the only difference is that nobody knew Know it is all in the open I would anticipate abalanced approach from Topol about EMRs, for example pointing out couple of benefits of EMRs in addition to the challenges they provided and was disappointed to read his bias over and over.The second drawback for me was the endorsement of couple new healthcare tech companies with dubious claims He did the same thing in his previous book The patient will see you now about Theranos He told how amazing this technology and how impressed he was for pages And we all know how Theranos ended upHe does the same thing for two new companies DayTwo and Viome, and in a similar way promotes a pretty ambitions claim that is yet to be proven and accepted Both companies are in search ofinvestors and the scientist are vary of wild claims made by these kinds of startups So it was a real turn off for me when I read an almost advertorial promotion of those, similar to what he did for Theranos.These two issues made me deduce two stars since I felt there was a certain bias in some of the issues and how they are being narrated.Other than these two, I think it is a good compilation of AI and its use in the industry and it s potentials I especially liked the section on AI Applications on Mental Health Definitely a must read for those who are interested in AI, Medicine and Health Informatics But read it with a grain of salt from time to time

  3. Sharon says:

    Well researched, eye opening and fascinating AI is the future of medicine and I think we need to embrace it and make sure that patients get the most out of it.

  4. Michael Halcon says:

    A very up to date and well researched book on the world of AI and its application in medicine.For someone with little knowledge about AI like myself, it gives a quick overview of AI, in what sectors AI tools are being used, and then proceeds to talk about its application within different branches of medicine, but also within other related areas such as drug discovery, omics and mental health.At the same time he also touches on issues of empathy in medicine and the patient doctor relationship A very up to date and well researched book on the world of AI and its application in medicine.For someone with little knowledge about AI like myself, it gives a quick overview of AI, in what sectors AI tools are being used, and then proceeds to talk about its application within different branches of medicine, but also within other related areas such as drug discovery, omics and mental health.At the same time he also touches on issues of empathy in medicine and the patient doctor relationship we can choose a technological solution to the profound human disconnection that exists today in healthcare

  5. Alina says:

    One way to describe modern medicine is shallow This book explores how AI would actually deepen in and how we should not be afraid of what it can bring to the table.

  6. Ardon Pillay says:

    With vast mountains of data generated every day, the medical profession is ripe for the application of deep learning to transform its very landscape From bringing precision medicine to life to improving the utility of electronic health records systems, the potential of AI to improve medicine for doctors and patients alike is extraordinary.The potential disruptive changes this might bring are also considered in the book, particularly with regards to the cries that we should stop training all rad With vast mountains of data generated every day, the medical profession is ripe for the application of deep learning to transform its very landscape From bringing precision medicine to life to improving the utility of electronic health records systems, the potential of AI to improve medicine for doctors and patients alike is extraordinary.The potential disruptive changes this might bring are also considered in the book, particularly with regards to the cries that we should stop training all radiologists now Topol suggests that new generations of radiologists will workas scan specialists, who work in tandem with AI to read pathological slides as well as MRIs, X rays and CT scans Unfortunately, the book feels somewhat choppy at times, feelinglike a collection of essays than a cohesive book However, I don t think that this is a significant problem the separation allows Topol to compartmentalise his thesis into its various subsections quite effectively He reminds us that AI may not just be able to build upon what is good and can be made excellent it can also help to fix the problem areas in medicine that have crept in over the years, in particular, time spent with patients Topol suggests that AI could help to maximise doctor patient interactions, by streamlining a lot of the various administrative processes that a doctor might have to attend to during a consultation It s a pertinent reminder that medicine is inherently a human enterprise, and that should not be forgotten in the pursuit of optimisation with deep learning To cure sometimes, to relieve often, to comfort always

  7. Wesley Pigg says:

    Eric Topol does a great job giving a broad overview of AI and the implications for healthcare I appreciated that he was able to talk broadly whilst also giving specific examples I also liked that I did not need to know much about artificial intelligence He starts by explaining the issues with the healthcare systems of today, which he sums up with the saying shallow medicine insufficient time, connection, data, and context in our consultations He then describes artificial intelligence and Eric Topol does a great job giving a broad overview of AI and the implications for healthcare I appreciated that he was able to talk broadly whilst also giving specific examples I also liked that I did not need to know much about artificial intelligence He starts by explaining the issues with the healthcare systems of today, which he sums up with the saying shallow medicine insufficient time, connection, data, and context in our consultations He then describes artificial intelligence and gives examples of the progress AI is making is specific areas of healthcare which is too broad to start listing He finishes with the idea that AI will undoubtedly change healthcare in the coming future, but will not replace the practitioner AI in healthcare can be used to either increase the productivity and efficiency of healthcare practitioners, or it can be used to give ustime with our patients He emphasises the importance of actively using this as an opportunity to make healthcare human again spendingtime with our patients, touching them, being empathetic, and connecting with them Key things that I took away from this book are We have to actively fight to ensure AI helps us connectwith our patients i.e havetime to be truly present in consultations , rather than just making usefficient and productive Completely autonomous AI doctors will likely never occur, but it will improve healthcare in incredible ways It is going to become increasingly important for healthcare professionals to have an understanding of AI

  8. Kristen says:

    Well, that was certainly an informative and insightful book about the use of artificial intelligence in healthcare However, I do admit that I skimmed some parts of it because I was mainly just looking for the applications For me, I did have prior knowledge about how AI works and some of its applications in medicine, but the author really does a good job in presenting some really cool uses that are being currently developed or will be in the future I really thank the author for compiling all Well, that was certainly an informative and insightful book about the use of artificial intelligence in healthcare However, I do admit that I skimmed some parts of it because I was mainly just looking for the applications For me, I did have prior knowledge about how AI works and some of its applications in medicine, but the author really does a good job in presenting some really cool uses that are being currently developed or will be in the future I really thank the author for compiling all this information into one book, too Eric Topol s argument other than talking about AI itself is that AI will make healthcare human again I think this is pretty valid doctors, at least in America, usually work in a high stress environment and time is restricted when speaking to patients This short amount of time 15 minutes is usually going to be mostly doing the things a machine can do, such as diagnosis or gathering information Instead, doctors should use that time caring for the patient with empathy and communication There are also some great points about how reliable AI is, especially if we re going to use it for life or death situations One of these problems is that we have no idea how an AI algorithm derives its conclusions How was it able to diagnose a disease so accurately, especially when a human cannot find the same signs What patterns led it to confirm this disease We have no idea, or at least not right now There are also major privacy concerns involving medical data if people use it for monitoring or similar technologies These are issues the world has to consider, so this isn t just a problem with researchers Anyway, it s very clear that Topol did his research I mean, just look at the notes works cited section I found this book extremely interesting and actually took notes Although I think anyone can enjoy it easy to understand and follow , I would recommend itto those who are interested in artificial intelligence

  9. Richard says:

    Ultimately, this is an optimistic book The greatest opportunity offered by AI is not reducing errors or workloads, or even curing cancer it is the opportunity to restore the precious and time honored connection and trust the human touch between patients and doctors There s detail on what machine learning can do right now That includes diagnosis from radiography, virutal medicine telemedicine and chatbots , personalisation of healthcare, diet, mental health, and AI as a tool for use by the Ultimately, this is an optimistic book The greatest opportunity offered by AI is not reducing errors or workloads, or even curing cancer it is the opportunity to restore the precious and time honored connection and trust the human touch between patients and doctors There s detail on what machine learning can do right now That includes diagnosis from radiography, virutal medicine telemedicine and chatbots , personalisation of healthcare, diet, mental health, and AI as a tool for use by the clinician I found it astonishing how much progress has been made Yet We re still in the earliest days of AI in medicine The field is long on computer algorithmic validation and promises but very short on real world, clinical proof of effectiveness Nevertheless, it is inevitable that narrow AI specific, targetting algorithms will take hold.My takeaway from the book was the hope for deep empathy knowing about the patient, their history, and having the time to use that knowledge It s our chance, perhaps the ultimate one, to bring back real medicine Presence Empathy Trust Caring Being Human

  10. Steve says:

    Eric Topol is always interesting be it a book, an interview, a podcast or on Twitter On Twitter to me he wins the MVT award for most valuable tweeter.This is I believe the third book of his that I ve read I am not a novice to AI ML and I lecture on these topics This is a very thorough book Almost every page is filled with information worth checking out even further It covers the current state of AI in medicine thoroughly From journal articles to companies carrying out the efforts I can t s Eric Topol is always interesting be it a book, an interview, a podcast or on Twitter On Twitter to me he wins the MVT award for most valuable tweeter.This is I believe the third book of his that I ve read I am not a novice to AI ML and I lecture on these topics This is a very thorough book Almost every page is filled with information worth checking out even further It covers the current state of AI in medicine thoroughly From journal articles to companies carrying out the efforts I can t see that there are omissions Visions of the future are usually speculative The vision of a speech recognition system assisting in writing a chart to help ease the burden of EHR is something I ve lectured to biomedical engineering students for several years Some day will likely happen.He speaks of AI ML as being an assist to the medical field rather than a replacement This is starting to happen and should be in practiceandbefore long The systems as assistant and not as replacement certainly makes a lot of sense.He isoptimistic than I that corporate medicine will allow doctors to spend their time demonstrating empathy and perhaps longer than 12 minutes Dr Topol also expresses the need to select medical studentson empathy and humanistic characteristics But several paragraphs later he said that we needphysicians to understand algorithm construction and be technical AI ML experts We need both but it is hard to be both And while you can look things up you need your medical database and experience in your head not on google.But overall I do not hesitate to give this book a five star rating It gives a view of the power of AI ML, where we are now and provides a vision of an idealistic possible future You will not learn how to do machine learning or have an outline of where to begin But that is not the task ofthis text There are many courses available online for that start with University of Washington and consider Andrew Ng at Stanford or several other institutions through MOOCs or degree programs

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