Deep Medicine: How artificial intelligence can make healthcare human again

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again "Can

A U T H O R : E R I C T O P O L E D I T I O N : F I R S T

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more human because of AI?"

Reviewed by Elan Somasundaram, PhD. Faculty in the Imaging Research Center and AI Core at Cincinnati Children’s Hospital Medical Center. See his research and publications here.

The rapid proliferation of Artificial Intelligence (AI) tools in healthcare is approaching a point in time where it is imperative for health care professionals and the general population to recognize the numerous ways in which data driven AI tools are poised to impact the practice of medicine and the way care is delivered. While the media coverage and most academic literature paint a rosy picture on the uncanny abilities of AI in healthcare and how they would transform medicine, the reality is more nuanced and requires extensive discussion, education, planning and rethinking of priorities such that this new era of AI augmented medicine is truly transformational and equitable to everyone involved in healthcare. Deep Medicine by Eric Topol is a comprehensive work that lays down the premise of AI in healthcare, how it could solve current challenges in medicine, and provides a list of desirable outcomes that should drive the design and adoption of AI systems in the clinic. The author presents his viewpoints substantiated with extensive literature survey and anecdotes derived from his long experience as a cardiologist, as a consultant for various AI initiatives, and from his encounters with the healthcare system as a patient.

Deep Medicine has 13 well-defined chapters. The first 3 chapters delve into the fundamental challenges faced by modern medicine and highlight the recent achievements in the field of AI using Machine Learning and Deep Learning algorithms. Introduction to Deep Medicine explains the complexities in making a correct disease diagnosis through real-world scenarios, especially given the large body of digital medical literature available today. It also provides insights into the tasks that could benefit by harnessing the power of AI and how such tools could be crucial in enabling healthcare providers focus their attention on the patient’ s well-being, both physical and emotional.

In chapter 2, Shallow Medicine, the author argues in detail the perils of some of the seemingly advanced technological adoptions in modern medicine such as the electronic health records system and the slew of diagnostic examinations that are at the physician ’ s disposal. The alarming numbers of reported misdiagnoses, unnecessary tests and imaging exams ordered give a wake-up call for active community participation in designing AI based healthcare tools such that they are efficient and effective in delivering their promise of improved quality of care. Medical diagnosis, the third chapter starts with a deep dive into the underlying principles of differential diagnosis as taught in medical schools. The author contends that System 1 thinking which leads to quick, intuitive diagnosis might not be the optimal strategy to train physicians for an era of personalized medicine and big data. This chapter also provides insights into the sources of uncertainties and biases in today ’ s medical diagnosis backed by relevant studies and statistics. Chapter 4 and 5 are dedicated to the subcategory of AI algorithms known as deep learning. Skinny on Deep Learning is a complete primer on the class of models that are the backbone of many recent AI tools that have demonstrated performance exceeding humans in various challenging tasks including image classification and natural language processing, two tasks that have numerous applications in healthcare. The evolution of neural networks, their basic architecture, types of learning strategies and definitions for related terminologies are presented in simple terms.

In Deep Liabilities, the focus is on the limitations, concerns, and compromises in adopting sophisticated AI tools, such as those powered by deep neural networks into the clinical workflow. The author makes a very important distinction that AI algorithms of today are only good at specific tasks, and they still lack the ability to seamlessly process contextual information. Issues related to availability of high-quality medical datasets, propagation of society ’ s inherent biases and inequities into training data leading to compromised AI models, protection of sensitive information and interpretability concerns due to the black-box nature of AI models are described in detail. In chapters 6-8, an in-depth discussion on the role of AI in various subspecialties of medicine are presented. AI in medical imaging has grown into its own field with Convolutional Neural Network architectures such as the U-net showcasing state-of-the-art performance on numerous tasks such as pneumonia detection in radiographs, organ delineation in 3dimensional cross-sectional images and cancer detection from pathology slides. Hence, in Doctors and Patterns, the achievements of AI in various imaging applications, especially in radiology and pathology are presented along with insights into how the physician ’ s job in these subspecialties would change with AI assisted workflows.

In Clinicians Without Patterns, all subspecialities that do not benefit directly from the superior pattern recognition abilities of AI algorithms but rely more on their ability to make predictions by embedding vast amount of information from multimodal datasets are discussed. Applications in this category span a broad spectrum ranging from accelerated image reconstruction, speech-to-text translation for notes taking, summarization of patient status from electronic health records and rare disease detection. In Mental Health, a detailed account of AI applications for pre-screening, diagnosis, phenotyping, and monitoring of patients with neural disorders using traditional clinical approaches such as speech and visual tests as well as innovative approaches based on digital data acquired from personal devices is discussed.

AI is also destined to have a major impact on healthcare systems such as enterprise software, patient management tools, workflow management, and insurance and billing platforms. An overview of the current state of such systems, their inefficiencies and AI based solutions that are being pursued are presented in AI and Health Systems. Chapters 10 and 11 focus on areas that are auxiliary to healthcare that are beginning to be redefined using AI techniques. Deep Discovery covers topics such as drug discovery, neuroscience, scientific research for disease identification and understanding, while Deep Diet focuses on various inroads made by data science towards personalized nutrition.

The Virtual Medical Assistant is an interesting chapter that puts forth the author ’ s vision on how the AI tools developed across multiple disciplines will culminate in an optimal assistant for managing one ’ s health and lifestyle. This chapter also brings to light the ownership and governance issues in managing personalized health data and behavioral challenges that need to be addressed before designing such sophisticated AI assistants. The final chapter, Deep Empathy, is a roundup of how the doctor-patient relationship has evolved over time and how the focus of any advanced AI adoption should be to strengthen this relationship which is vital to improve the experience for the patients, physicians, care givers and families. Overall, this book provides “deep ” insights into some of the pitfalls of current medical practice through real-world examples that are relatable to most people that have interacted with the American healthcare system. The latest boom in AI capabilities has given a lot of hope to address many of the limitations in healthcare and this book does a good job of summarizing them from a neutral standpoint. While some of the AI case studies and applications cited in this book might already be outdated due to the rapid progress in this field, this book is a treasure with a lot of valuable information for physicians, researchers, hospital administrators and the general audience.

"This book is a treasure with a lot of valuable information for physicians, researchers, hospital administrators and the general audience. "