Artificial Intelligence On Medical Data
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| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
| Author | : Enrico Guardelli |
| Publisher | : Clube de Autores |
| Total Pages | : 164 |
| Release | : 2024-05-22 |
| Genre | : Medical |
| ISBN | : |
Artificial Intelligence (AI) has emerged as a powerful ally in the healthcare sector, revolutionizing the way medical professionals diagnose, treat, and manage diseases. By integrating advanced machine learning algorithms and natural language processing, AI has demonstrated its ability to swiftly and accurately analyze vast medical datasets, providing valuable insights that can lead to more precise diagnoses and effective treatments. From interpreting medical imaging to real-time patient monitoring, the applications of AI in healthcare are vast and multifaceted, promising to significantly enhance the quality of medical care and ultimately save lives. In this book Artificial Intelligence in Healthcare: Next Frontier you will gain a comprehensive overview of how medtechs are leading the way in applying artificial intelligence (AI) in the healthcare sector. These companies are at the forefront of innovation, exploring AI s potential to improve healthcare worldwide. By examining these startups, we can learn much about AI s potential in healthcare and how it is shaping the future of the industry. Through ongoing research and development efforts, these companies are helping to pave the way for more effective, accessible, and personalized healthcare for all.
| Author | : Natasha H. Williams |
| Publisher | : Springer Nature |
| Total Pages | : 121 |
| Release | : 2024-01-01 |
| Genre | : Philosophy |
| ISBN | : 303148262X |
This book explores the ethical problems of algorithmic bias and its potential impact on populations that experience health disparities by examining the historical underpinnings of explicit and implicit bias, the influence of the social determinants of health, and the inclusion of racial and ethnic minorities in data. Over the last twenty-five years, the diagnosis and treatment of disease have advanced at breakneck speeds. Currently, we have technologies that have revolutionized the practice of medicine, such as telemedicine, precision medicine, big data, and AI. These technologies, especially AI, promise to improve the quality of patient care, lower health care costs, improve patient treatment outcomes, and decrease patient mortality. AI may also be a tool that reduces health disparities; however, algorithmic bias may impede its success. This book explores the risks of using AI in the context of health disparities. It is of interest to health services researchers, ethicists, policy analysts, social scientists, health disparities researchers, and AI policy makers.
| Author | : David Riaño |
| Publisher | : Springer |
| Total Pages | : 431 |
| Release | : 2019-06-19 |
| Genre | : Computers |
| ISBN | : 303021642X |
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.
| Author | : Lei Xing |
| Publisher | : Academic Press |
| Total Pages | : 570 |
| Release | : 2020-09-03 |
| Genre | : Medical |
| ISBN | : 0128212586 |
Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach
| Author | : Anthony C. Chang |
| Publisher | : Academic Press |
| Total Pages | : 549 |
| Release | : 2020-06-27 |
| Genre | : Science |
| ISBN | : 0128233389 |
Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare
| Author | : Arjun Panesar |
| Publisher | : Apress |
| Total Pages | : 390 |
| Release | : 2019-02-04 |
| Genre | : Computers |
| ISBN | : 1484237994 |
Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
| Author | : Niklas Lidströmer |
| Publisher | : Springer |
| Total Pages | : 1816 |
| Release | : 2022-03-17 |
| Genre | : Medical |
| ISBN | : 9783030645724 |
This book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.
| Author | : Eric Topol |
| Publisher | : Basic Books |
| Total Pages | : 373 |
| Release | : 2019-03-12 |
| Genre | : Health & Fitness |
| ISBN | : 1541644646 |
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.
| Author | : Kayvan Najarian |
| Publisher | : CRC Press |
| Total Pages | : 300 |
| Release | : 2022-04-06 |
| Genre | : Computers |
| ISBN | : 1000565815 |
This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.
