7 books on AI for Medicine [PDF]

Updated: March 21, 2024

Books on AI for Medicine are invaluable resources for startups venturing into the development of AI solutions for healthcare. They provide an essential foundation by covering the intersection of artificial intelligence and medical practices, encompassing areas like medical imaging analysis, drug discovery, predictive analytics, and patient care optimization. These resources delve into advanced machine learning algorithms, data privacy and ethical considerations, and regulatory aspects unique to the healthcare industry. Moreover, these books often include case studies and real-world examples of AI implementation in medicine, offering insights into successful applications and best practices.

1. AI and Blockchain in Healthcare
2023 by Bipin Kumar Rai, Gautam Kumar, Vipin Balyan



This book offers an in-depth exploration of the latest advancements in blockchain and AI technologies within the healthcare sector. The healthcare industry is rapidly integrating blockchain and AI solutions, marking significant progress. Today, AI, machine learning, deep learning, and blockchain are making substantial impacts across various domains. These cutting-edge applications are driving positive transformations in healthcare. Blockchain, a decentralized communication platform, holds the potential to revolutionize data storage and information management, potentially reducing the role of intermediaries, a crucial regulatory entity in our society. Transactions benefit from simultaneous security and trustworthiness through the application of cryptographic principles. In recent times, blockchain technology has gained widespread attention, extending its influence into various sectors, primarily due to the popularity of cryptocurrencies. Among the fields where blockchain technology exhibits immense potential, healthcare stands out due to its pressing need for a more patient-centered approach. It aims to connect disparate systems and enhance the accuracy of electronic healthcare records (EHRs).
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2. Recent Advances in AI-enabled Automated Medical Diagnosis
2022 by Richard Jiang, Li Zhang, Hua-Liang Wei, Danny Crookes, Paul Chazot



The past decade has witnessed remarkable progress in the field of AI-enabled automated medical diagnosis, primarily due to advancements in deep learning. This progress signifies a transformative phase for both medical research and the healthcare industry. Researchers engaged in the development and implementation of advanced machine learning methods for medical and clinical challenges are currently operating in a prolific era. This book serves as a comprehensive resource, spotlighting the latest significant breakthroughs in this interdisciplinary field, and aims to disseminate these cutting-edge advancements to a broad audience encompassing experts, researchers, students, industry professionals, and healthcare providers.
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3. Evolving Predictive Analytics in Healthcare: New AI Techniques for Real-time Interventions
2022 by Abhishek Kumar, Ashutosh Kumar Dubey, Surbhi Bhatia, Swarn Avinash Kumar, Dac-Nhuong Le



"In this book, the application of practical predictive analytics in the healthcare domain, specifically for the diagnosis of current diseases, is explored, with a primary emphasis on medical imaging. Harnessing the advancements in AI, IoT, and data analytics, the book underscores the capacity to address real-time medical challenges, with an intensified focus on early prediction employing machine learning and deep learning algorithms. By integrating the capabilities of artificial intelligence with the Internet of 'Medical' Things, these algorithms can process patient data and characteristics, providing forecasts regarding future diagnoses, classifications, treatment strategies, and associated costs."
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4. AI-First Healthcare
2021 by Kerrie L. Holley, Siupo Becker M.D.



In this practical guide, Kerrie Holley and Siupo Becker offer insights into the current and prospective applications of AI in addressing critical healthcare issues. The book serves as a valuable resource for informatics and healthcare leaders, empowering them to formulate AI strategies and implementation plans for the healthcare sector. By leveraging this resource, business stakeholders and practitioners can acquire the knowledge, roadmap, and confidence needed to support AI initiatives within their organizations, without delving into algorithmic intricacies or open-source frameworks. Co-authored by an AI expert and a medical doctor who harnesses AI to tackle healthcare's most complex challenges, the book explores topics such as the realities of AI, human-centered AI, diverse AI technologies, IoT and ambient computing in patient care, waste reduction in healthcare, AI strategy, and the identification of high-priority AI applications.
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5. AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services
2021 by Robert Shimonski



Authored by a renowned technology executive specializing in healthcare IT, this book offers tangible illustrations and pragmatic guidance for the implementation of artificial intelligence solutions within your healthcare IT environment. "AI in Healthcare" exposes readers to the opportunities presented by real-time event correlation and response automation, facilitating the reduction of IT disruptions in critical healthcare IT functions. The book provides an extensive exploration of vital and central subjects in the application of artificial intelligence in healthcare, encompassing Healthcare IT AI, Clinical Operations AI, Operational Infrastructure, Project Planning, Metrics, Reporting, Service Performance, AIOps in Automation, AIOps Cloud Operations, and a glimpse into the Future of AI. Written in a comprehensible and straightforward manner, this book will prove to be an invaluable resource for IT managers, administrators, and engineers operating in healthcare settings, as well as individuals with an interest or stake in healthcare technology.
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6. Explainable AI in Healthcare and Medicine: Building a Culture of Transparency and Accountability
2020 by Arash Shaban-Nejad, Martin Michalowski, David L. Buckeridge



This book provides insights into the most recent developments in applying artificial intelligence and data science to healthcare and medicine. Drawing from the 2020 Health Intelligence Workshop, which was part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it presents an overview of the key issues, challenges, and opportunities in this field, accompanied by the latest research discoveries. It delves into various practical applications, making emerging subjects like digital health and explainable AI in healthcare and medicine accessible to a wide audience. The availability of models that are explainable and interpretable represents the initial phase in fostering a culture of transparency and accountability within healthcare. Therefore, this book serves as a valuable resource for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in both the theory and implementation of computational models for public and personalized health intelligence.
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7. Healthcare and Artificial Intelligence
2020 by Bernard Nordlinger, ‎Cédric Villani, ‎Daniela Rus



This book offers a comprehensive perspective on the integration of AI into medicine, addressing the confluence of mathematics, informatics, and healthcare. It is designed to benefit both AI specialists, providing them with a retrospective view and a forward-looking outlook, as well as individuals without specialized expertise who have an interest in this timely and significant field. The objective is to present a lucid, impartial, and rational exploration of the topics under discussion, steering clear of any unrealistic expectations associated with the concept of "AI." Moreover, the book aims to provide a panoramic overview rather than delving into intricate technical minutiae.
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