Download Free Deep Medicine Book in PDF and EPUB Free Download. You can read online Deep Medicine and write the review.

A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.
A professor of medicine reveals how technology like wireless internet, individual data, and personal genomics can be used to save lives.
Raj Patel, the New York Times bestselling author of The Value of Nothing, teams up with physician, activist, and co-founder of the Do No Harm Coalition Rupa Marya to reveal the links between health and structural injustices--and to offer a new deep medicine that can heal our bodies and our world. The Covid pandemic and the shocking racial disparities in its impact. The surge in inflammatory illnesses such as gastrointestinal disorders and asthma. Mass uprisings around the world in response to systemic racism and violence. Rising numbers of climate refugees. Our bodies, societies, and planet are inflamed. Boldly original, Inflamed takes us on a medical tour through the human body—our digestive, endocrine, circulatory, respiratory, reproductive, immune, and nervous systems. Unlike a traditional anatomy book, this groundbreaking work illuminates the hidden relationships between our biological systems and the profound injustices of our political and economic systems. Inflammation is connected to the food we eat, the air we breathe, and the diversity of the microbes living inside us, which regulate everything from our brain’s development to our immune system’s functioning. It’s connected to the number of traumatic events we experienced as children and to the traumas endured by our ancestors. It’s connected not only to access to health care but to the very models of health that physicians practice. Raj Patel, the renowned political economist and New York Times bestselling author of The Value of Nothing, teams up with the physician Rupa Marya to offer a radical new cure: the deep medicine of decolonization. Decolonizing heals what has been divided, reestablishing our relationships with the Earth and one another. Combining the latest scientific research and scholarship on globalization with the stories of Marya’s work with patients in marginalized communities, activist passion, and the wisdom of Indigenous groups, Inflamed points the way toward a deep medicine that has the potential to heal not only our bodies, but the world.
This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.
The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
Deep Healing brings new hope to every reader. It awakens even the most skeptical among us to the miraculous inborn, self-healing capacities of our mind-body. Emmett Miller, M.D., practicing as a traditional family doctor for 20 years, discovered that when a part of your body is sick, the whole body system is out of balance. He saw that how his patients thought about and saw life, affected and seemed to create whatever their current state of health was. He has stated that it is not enough to heal the particular illness without understanding the emotional and psychological basis for the ailment or problem. We must heal the entire person...not just a specific part. Dr. Miller has had great success with guided imagery to promote physical health and emotional well-being. He has even been successful using guided imagery to do minor surgery without any anesthetic, again proving the mind/body connection, and the control of our bodies by our thoughts. Through the presentation of stories, reflections, and case studies, Dr. Miller presents his wonderful, deep healing theories that will instill a new sense of hope and optimism into all who read this book.
Little more than one hundred years ago, maps of the world still boasted white space: places where no human had ever trod. Within a few short decades the most hostile of the world’s environments had all been conquered. Likewise, in the twentieth century, medicine transformed human life. Doctors took what was routinely fatal and made it survivable. As modernity brought us ever more into different kinds of extremis, doctors pushed the bounds of medical advances and human endurance. Extreme exploration challenged the body in ways that only the vanguard of science could answer. Doctors, scientists, and explorers all share a defining trait: they push on in the face of grim odds. Because of their extreme exploration we not only understand our physiology better; we have also made enormous strides in the science of healing. Drawing on his own experience as an anesthesiologist, intensive care expert, and NASA adviser, Dr. Kevin Fong examines how cuttingedge medicine pushes the envelope of human survival by studying the human body’s response when tested by physical extremes. Extreme Medicine explores different limits of endurance and the lens each offers on one of the systems of the body. The challenges of Arctic exploration created opportunities for breakthroughs in open heart surgery; battlefield doctors pioneered techniques for skin grafts, heart surgery, and trauma care; underwater and outer space exploration have revolutionized our understanding of breathing, gravity, and much more. Avant-garde medicine is fundamentally changing our ideas about the nature of life and death. Through astonishing accounts of extraordinary events and pioneering medicine, Fong illustrates the sheer audacity of medical practice at extreme limits, where human life is balanced on a knife’s edge. Extreme Medicine is a gripping debut about the science of healing, but also about exploration in its broadest sense—and about how, by probing the very limits of our biology, we may ultimately return with a better appreciation of how our bodies work, of what life is, and what it means to be human.
The essential guide by one of America's leading doctors to how digital technology enables all of us to take charge of our health A trip to the doctor is almost a guarantee of misery. You'll make an appointment months in advance. You'll probably wait for several hours until you hear "the doctor will see you now"-but only for fifteen minutes! Then you'll wait even longer for lab tests, the results of which you'll likely never see, unless they indicate further (and more invasive) tests, most of which will probably prove unnecessary (much like physicals themselves). And your bill will be astronomical. In The Patient Will See You Now, Eric Topol, one of the nation's top physicians, shows why medicine does not have to be that way. Instead, you could use your smartphone to get rapid test results from one drop of blood, monitor your vital signs both day and night, and use an artificially intelligent algorithm to receive a diagnosis without having to see a doctor, all at a small fraction of the cost imposed by our modern healthcare system. The change is powered by what Topol calls medicine's "Gutenberg moment." Much as the printing press took learning out of the hands of a priestly class, the mobile internet is doing the same for medicine, giving us unprecedented control over our healthcare. With smartphones in hand, we are no longer beholden to an impersonal and paternalistic system in which "doctor knows best." Medicine has been digitized, Topol argues; now it will be democratized. Computers will replace physicians for many diagnostic tasks, citizen science will give rise to citizen medicine, and enormous data sets will give us new means to attack conditions that have long been incurable. Massive, open, online medicine, where diagnostics are done by Facebook-like comparisons of medical profiles, will enable real-time, real-world research on massive populations. There's no doubt the path forward will be complicated: the medical establishment will resist these changes, and digitized medicine inevitably raises serious issues surrounding privacy. Nevertheless, the result-better, cheaper, and more human health care-will be worth it. Provocative and engrossing, The Patient Will See You Now is essential reading for anyone who thinks they deserve better health care. That is, for all of us.
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.