Artificial Intelligence in Healthcare Kindle Edition

This book is a wonderful overview of how Artificial Intelligence is already being employed in our health care system, and how it may be used in the future. The criticism that this book does not go deeply enough into the issue is counter productive and unfair; the author states that his main objective with this book is to help ordinary people better understand this complicated issue.There are many advantages from which we all benefit from this advancing technology. Much of it eliminates the need for human beings to perform basic tasks. The list of these services for the medical field seems endless. The author gives specific examples such as as new technology called SkinVision which can detect skin cancer by recognizing moles and skin lesions, Microsure, which creates robots to perform microsurgeries. One most of us is familiar with: the Apple watch, a personal item that performs an EKG, thereby assisting doctors treating patients with heart disease. Robotics can perform simple tasks such as alerts and reminders, reading images and aiding in interpretation, retrieving information for doctors, and handling closings/stiches in the operation theater.Scary stuff, to me, I confess. But the author assures us that final responsibility for medical decisions will remain with doctors, ensuring that AI never has final control. Can we trust that? Enormous progress has been made in this field in the last ten years, and with that comes great concerns about the dangers of unimpeded, uncontrolled Artificial Intelligence technology.After all, Elon Musk has stated unequivocally that we should be very careful.The author describes the various obstacles that exist to slow the full potential of AI in health care. Privacy issues, ethical questions, and the huge necessary investment costs are just three of these. So from my point of view, it is a good thing this whole process may be slowed down by these hurdles, as trusting human beings to protect us may be a dangerous proposition.This book is excellent coverage of the topic, and is well researched and laid out in an easy-to-read fashion.

Artificial Intelligence in Healthcare provides a broad survey of companies, technologies, and cutting edge advances that are emerging to benefit healthcare. The author even tackles an explanation of the processes for ML/DL and how they are applied to various aspects of medicine in all its big data glory. The author writes in a clear, well organized manner making the broad topic easy to follow, but feels repetitive at times, often covering the same topic multiple times, almost as if two books were combined into one larger work. That was my only complaint to another wise well researched work on an important topic. I recommend it.

An ambitious overview of AI in the healthcare industry—and, I might add, a bold one since books like this are quick to go out of date. If you know nothing about AI and are in the healthcare industry or know about AI but are new to the healthcare industry, then this book is for you. The only audience this would not be for is someone who knows both unless they’re trying to keep up with trends or lists of what other people are talking about.(Note: I notice that the one-star reviews are from academic uses, which is the wrong audience for this book; this book is for leaders in the industry who need to keep abreast of the technology, vendors, and use cases even though they're not knowledgeable in the field of AI and so am rating it based on that use case and not the academic use case that would lead someone to review the which-vendor-is-doing-what-in-the-space content to be useless to them)The only reason that it’s not for people who are experts in both is because the book is really just a set of descriptions of the capabilities, considerations, etc. and what you can generally presume from that. It doesn’t go much into the tech or the data science (though it does introduce people to how the data science works where appropriate), so it’s not for that purpose. Overall, if you just wanted a list of use cases and enough explanation to sound intelligent when you go back and have a conversation with data scientists at your organization, it’s a good start. Just don’t be that person who goes and acts like they know more than they do (i.e., like when leaders go to IT and point to a magazine ad for an ERP system), and you should have a great conversation with the data science team.What I Liked:-It covers what you’d want to see: categories of AI use, ethics, myths vs. reality, trends, future possibilities, etc. It also covers specific areas (e.g., pathology, surgery). What’s really good about this latter piece is that it covers the progress made in the field and when they occurred, so you can get a decent sense of how mature these emerging capabilities are at this point. It’s not everything, but it’s exactly enough given that the book has to remain a reasonable length and be more for industry experts than people who are going to get a data science position tomorrow to push that specific innovation.-It talks about things like NVIDIA’s innovation in the graphics world affecting capabilities. Very nice angles that many people wouldn’t even think about monitoring without the knowledge of the tech space or the graphic-intensive parts of the industry.-Tries to cover the benefits and some risks or concerns, with a greater focus on use cases (everyone’s favorite topic, so I don’t blame the author for going right after those) than any kind of deep analysis or predictions on any specific item. Again, if you’re a leader and want to stay abreast, this is probably what you want and then you can go get more detail on the areas of interest from other sources or your data science/IT team.Nitpicks:-Arguably, some of the apps provided early on aren’t AI per se (at least, not the functionality described, so I could just be unfamiliar with the AI part of it). They mentioned things like talking to your doctor via video chat for example. You don’t need any AI for that—that’s just a basic app. Maybe the author was just describing the evolution, but that could’ve been mentioned. These were intermixed with AI-based apps for diagnosis, for example, which are AI-powered. So it might be that the apps that didn’t have any AI functionality mentioned did use it…but it might confuse someone new to AI into thinking that all mobile apps are AI.-Myth #2 isn’t really a myth; models are biased if the data is biased, and it can be very difficult to eliminate biases. So the idea that this is simple is oversold.-This is a real nitpick, but technically a lot of the points were pretty much common sense if you know anything about what computers can do and what they’re not as good at people at doing. For example, we know from automation over the last century that computers are better at repetitive tasks where accuracy is necessary, and humans are better at responding in the moment to new and unexpected situations. We know that bad data will give you bad results from the “garbage in, garbage out” mantra of IT for the last several decades. So it’s no surprise that most of the applications of AI in Healthcare can probably be traced back to some of these classic points. Examples include that models aren’t inherently biased but the data can make them that way (“garbage in, garbage out”) and that AI can be used to surface patterns to predict certain conditions (yes, that’s literally what Siri does and everyone would know that use case could apply to anything). That said, that’s not really a dig on the book at all since it’s listing what you need to know, and a lot of what you need to know is that a lot of trends will just be new takes on old concepts. Plus, it’s great that the author doesn’t assume that the reader would intuit a lot of these applications because you never know what people don’t know or haven’t thought about.-Another nitpick that’s not really a knock on the book: the speed of change makes it difficult to keep up. For example, the book is on Apple Watch Series 4 (note: it refers to it informally as the iWatch, which isn’t true but is possibly just being cute), and the 6 just came out.-Some of the chapters are dedicated to specific vendor technologies. Might not be perfect for you if you want an objective assessment of the technology, but again you probably just want to know some of these trends and so this is what I’d call “author’s discretion” as to whether to focus on the tech or the organization/solution if it’s notable and, in the author’s opinion, leading the change.-In the conclusion, it says that some people believe that AI is a “necessary evil”. I don’t believe that any legitimate experts in the space believe that, so it seems like a little bit of creating a false sense of controversy when there is none. Maybe the author meant that everyone sees its potential benefit but some see its outstanding, potentially catastrophic risks. If that’s what the author meant, then that’s correct, but readers won’t necessarily get that from the figure of speech “necessary evil”.Other Thoughts:-I was waiting for the risks/kinks of AI in healthcare. My favorite example is that an ML algorithm identified moles/skin lesions that had rulers next to them in their photos as more likely to be cancerous. Clearly, the ruler has nothing to do with whether a mole is cancerous, but the AI will be inaccurate if someone takes a photo without the ruler.-Note: While it does not impact my review at all, I should probably note that I do work for a company that evaluates vendors in the AI space but am not an employee that actually does said evaluations (nor do I interact with the people who do on the topic of vendors in any way that influences their evaluations). Nor do I take an opinion on any vendors in this review. The only bias I could have would be to put down this commentary and recommend my organization, which I did not and have not, so clearly there’s no influence from that association. But it’s ethical to note this so there’s no perception of bias or conflict of interest by not disclosing it.-Edits: Misspells Barack Obama in the upfront quotations. Missing a quotation mark at the end of software-as-a-service on (what Kindle tells me is) page 150.

I feel liberated whenever I get the opportunity to read and write about a buzzing technology like AI or IoT or something else. I feel like going on and on….no stopping. Today, I will be gossiping about AI in the guise of Dr. Parag Mahajan’s masterpiece - Artificial Intelligence in Healthcare.The second edition of "Artificial Intelligence in Healthcare" by Parag Mahajan is definitely a must read book for everyone working in the health care sector. It gives latest information about the role of artificial intelligence in improving the efficiency of services in the health care organizations. Almost all important issues and advances in the rapidly changing field of AI in medicine and public health are covered. It includes topics about ethical considerations of AI in healthcare and myths about AI. It gives ample examples of current and planned health care AI products and services. It makes an important conclusion that AI is not to replace the healthcare professionals, but is a tool that complements and extends their capabilities to diagnose, treat and monitor diseases.I recommend this book to everyone in the healthcare and the AI/ML/DL/Data Science sectors. The use of technology, Artificial Intelligence, is presently spreading rapidly in medical research. According to studies, the volume of health data is growing at a phenomenal rate: 2314 Exabyte of data estimated for 2020, an annual growth rate of at least 48% and exploiting the potential of these data, thanks to the AI technologies, which opens an alternate way to the traditional diagnosis and better patient care.The National Geographic magazine of January 2019 devotes a complete file to "Medicine of the future." This topic is described as medicine where robotics and connected objects are in the foreground: a contact lens capable of measuring blood glucose in the tears of a diabetic patient, a patch that measures blood pressure and sends the collected data directly to a laptop system, etc. Thus, these facts reviewed an unforeseen future of different Artificial Intelligence (AI) technologies, which suggest digital and personalized medicine. That is why health data, particularly on this subject, has become a topical issue of numerous research projects, particularly on complex pathologies to diagnose.It is a tremendous information-packed book that is professionally written out of intensive knowledge and researches about the efficacy and development in the application of Artificial Intelligence in healthcare practices. This is a potent guide that widens the knowledge of the people about the relationship between Artificial Intelligence (AI) and healthcare with straightforward, concise language. It also provides a detailed understanding of how AI is improving healthcare in our contemporary society.Highly recommended!

Informative book on Artificial Intelligence and its application in medical field. The book is divided into parts which enables the readers to understand the section without any confusion. Though the book contains some technical terms, the book can be comprehended by the ordinary public also. I was quite unaware about the developments of AI in medicine. But after reading the book I have an intermediate knowledge of its functioning and such. AI is going to be the base of the futuristic world and therefore, I would recommend everyone to buy this book in order to have a proper understanding about it.