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5 Best books on AI for Medicine and Healthcare
May 21, 2023 | Author: Maria Lin
Here is my list of 5 most interesting books about artificial intelligence for Health:
1. The Future of Healthcare: Humans and Machines Partnering for Better Outcomes
This book has a reminiscent quality of a brainstorming session or a collection of bookmarks. It presents numerous intriguing ideas and ongoing projects without delving deeply into analysis or discussing failed efforts, such as the absence of mention about Theranos. The author appears to hold strong belief in the ability of consumer-oriented tech companies like Amazon, Apple, and Google to tackle and resolve healthcare challenges, although only time will tell if those expectations are met. If you have an interest in exploring how technological advancements could potentially enhance healthcare, this book is worth reading.
2. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
This book presents an exceptional exploration of the immense potential of AI to revolutionize the field of medicine, while also acknowledging the potential challenges and transitional difficulties. Some sections of the book primarily serve as summaries of numerous studies conducted using machine learning in specific medical domains, with limited additional analysis provided by the author. As someone working in the field who was already familiar with most of these studies, I found these parts of the book somewhat tedious. However, for readers who are new to the subject, these sections can serve as an eye-opening introduction to the remarkable achievements of machine learning in healthcare thus far. The true value of this book, in my opinion, lies in the author's discussions on how AI can be effectively harnessed to enhance medicine for both patients and healthcare professionals. It offers a refreshing perspective, countering the prevalent "robots are taking over our jobs" narrative, and provides a thought-provoking read that is well worth your time.
3. Artificial Intelligence in Healthcare
This book offers an extensive examination of the utilization and ethical implications of Artificial Intelligence in healthcare, along with highlighting the innovative advancements in the health sector related to AI. It provides detailed information on current and planned AI healthcare products and services through typical examples. As a result, the book reaches a remarkable conclusion: the emergence of Artificial Intelligence is not intended to replace healthcare professionals in their roles but rather to serve as a tool that enhances and complements their abilities in diagnosing, treating, and monitoring diseases. The ultimate goal is to achieve uninterrupted healthcare efficacy.
4. Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
This book serves as a comprehensive guide that explores various aspects of machine learning algorithms, architectural design, and their applications in healthcare and big data challenges. It not only covers technical aspects but also delves into the ethical implications of healthcare data analytics and discusses the future prospects of AI in optimizing population and patient health. The book provides valuable insights on creating machine learning models, assessing their performance, and implementing their outcomes effectively within an organization. It also offers techniques for applying machine learning within your specific organizational context, enabling you to evaluate the effectiveness, suitability, and efficiency of AI applications. The content is enriched with illustrative case studies, including a focus on how patient-led data learning is redefining the management of chronic diseases.
5. Demystifying Big Data and Machine Learning for Healthcare
For Healthcare IT professionals who are interested in the intersection of Machine Learning, AI, and Big Data in the healthcare industry, this book is an essential read. The authors have effectively compiled a collection of real-life examples from various healthcare providers in the United States. These case studies offer valuable insights into the current landscape of big data, machine learning, and AI in healthcare, as well as provide perspectives on what the future holds for healthcare professionals and policymakers. With eight comprehensive case studies, the book not only reflects the current reality but also anticipates the developments that lie ahead. I highly recommend this book to anyone involved in or planning to engage in Healthcare Analytics projects.
See also: Top 10 eBook Organizers
1. The Future of Healthcare: Humans and Machines Partnering for Better Outcomes
This book has a reminiscent quality of a brainstorming session or a collection of bookmarks. It presents numerous intriguing ideas and ongoing projects without delving deeply into analysis or discussing failed efforts, such as the absence of mention about Theranos. The author appears to hold strong belief in the ability of consumer-oriented tech companies like Amazon, Apple, and Google to tackle and resolve healthcare challenges, although only time will tell if those expectations are met. If you have an interest in exploring how technological advancements could potentially enhance healthcare, this book is worth reading.
2. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
This book presents an exceptional exploration of the immense potential of AI to revolutionize the field of medicine, while also acknowledging the potential challenges and transitional difficulties. Some sections of the book primarily serve as summaries of numerous studies conducted using machine learning in specific medical domains, with limited additional analysis provided by the author. As someone working in the field who was already familiar with most of these studies, I found these parts of the book somewhat tedious. However, for readers who are new to the subject, these sections can serve as an eye-opening introduction to the remarkable achievements of machine learning in healthcare thus far. The true value of this book, in my opinion, lies in the author's discussions on how AI can be effectively harnessed to enhance medicine for both patients and healthcare professionals. It offers a refreshing perspective, countering the prevalent "robots are taking over our jobs" narrative, and provides a thought-provoking read that is well worth your time.
3. Artificial Intelligence in Healthcare
This book offers an extensive examination of the utilization and ethical implications of Artificial Intelligence in healthcare, along with highlighting the innovative advancements in the health sector related to AI. It provides detailed information on current and planned AI healthcare products and services through typical examples. As a result, the book reaches a remarkable conclusion: the emergence of Artificial Intelligence is not intended to replace healthcare professionals in their roles but rather to serve as a tool that enhances and complements their abilities in diagnosing, treating, and monitoring diseases. The ultimate goal is to achieve uninterrupted healthcare efficacy.
4. Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
This book serves as a comprehensive guide that explores various aspects of machine learning algorithms, architectural design, and their applications in healthcare and big data challenges. It not only covers technical aspects but also delves into the ethical implications of healthcare data analytics and discusses the future prospects of AI in optimizing population and patient health. The book provides valuable insights on creating machine learning models, assessing their performance, and implementing their outcomes effectively within an organization. It also offers techniques for applying machine learning within your specific organizational context, enabling you to evaluate the effectiveness, suitability, and efficiency of AI applications. The content is enriched with illustrative case studies, including a focus on how patient-led data learning is redefining the management of chronic diseases.
5. Demystifying Big Data and Machine Learning for Healthcare
For Healthcare IT professionals who are interested in the intersection of Machine Learning, AI, and Big Data in the healthcare industry, this book is an essential read. The authors have effectively compiled a collection of real-life examples from various healthcare providers in the United States. These case studies offer valuable insights into the current landscape of big data, machine learning, and AI in healthcare, as well as provide perspectives on what the future holds for healthcare professionals and policymakers. With eight comprehensive case studies, the book not only reflects the current reality but also anticipates the developments that lie ahead. I highly recommend this book to anyone involved in or planning to engage in Healthcare Analytics projects.
See also: Top 10 eBook Organizers
