Download or read book Artificial Intelligence for Data Driven Medical Diagnosis written by Deepak Gupta and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-02-08 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book MoneyBall Medicine written by Harry Glorikian and published by Taylor & Francis. This book was released on 2017-11-20 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can a smartwatch help patients with diabetes manage their disease? Why can’t patients find out prices for surgeries and other procedures before they happen? How can researchers speed up the decade-long process of drug development? How will "Precision Medicine" impact patient care outside of cancer? What can doctors, hospitals, and health systems do to ensure they are maximizing high-value care? How can healthcare entrepreneurs find success in this data-driven market? A revolution is transforming the $10 trillion healthcare landscape, promising greater transparency, improved efficiency, and new ways of delivering care. This new landscape presents tremendous opportunity for those who are ready to embrace the data-driven reality. Having the right data and knowing how to use it will be the key to success in the healthcare market in the future. We are already starting to see the impacts in drug development, precision medicine, and how patients with rare diseases are diagnosed and treated. Startups are launched every week to fill an unmet need and address the current problems in the healthcare system. Digital devices and artificial intelligence are helping doctors do their jobs faster and with more accuracy. MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market, which includes interviews with dozens of healthcare leaders, describes the business challenges and opportunities arising for those working in one of the most vibrant sectors of the world’s economy. Doctors, hospital administrators, health information technology directors, and entrepreneurs need to adapt to the changes effecting healthcare today in order to succeed in the new, cost-conscious and value-based environment of the future. The authors map out many of the changes taking place, describe how they are impacting everyone from patients to researchers to insurers, and outline some predictions for the healthcare industry in the years to come.

Download or read book Diverse Perspectives and State of the Art Approaches to the Utilization of Data Driven Clinical Decision Support Systems written by Connolly, Thomas M. and published by IGI Global. This book was released on 2022-11-11 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: The medical domain is home to many critical challenges that stand to be overcome with the use of data-driven clinical decision support systems (CDSS), and there is a growing set of examples of automated diagnosis, prognosis, drug design, and testing. However, the current state of AI in medicine has been summarized as “high on promise and relatively low on data and proof.” If such problems can be addressed, a data-driven approach will be very important to the future of CDSSs as it simplifies the knowledge acquisition and maintenance process, a process that is time-consuming and requires considerable human effort. Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems critically reflects on the challenges that data-driven CDSSs must address to become mainstream healthcare systems rather than a small set of exemplars of what might be possible. It further identifies evidence-based, successful data-driven CDSSs. Covering topics such as automated planning, diagnostic systems, and explainable artificial intelligence, this premier reference source is an excellent resource for medical professionals, healthcare administrators, IT managers, pharmacists, students and faculty of higher education, librarians, researchers, and academicians.

Download or read book The Data Driven Doctor written by Henry E Parkins and published by Independently Published. This book was released on 2024-04-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing "The Data-Driven Doctor: How AI is Transforming Medicine" Your Essential Guide to the Future of Healthcare! Embark on a groundbreaking journey into the world of artificial intelligence (AI) and medicine with "The Data-Driven Doctor." In this captivating book, you'll discover the transformative power of AI in reshaping the future of healthcare delivery, clinical decision-making, and patient care. From early disease detection to personalized treatment approaches, AI is revolutionizing every aspect of medicine, offering unprecedented opportunities to improve patient outcomes, enhance clinical efficiency, and drive innovation in healthcare. Through real-world examples, cutting-edge research, and expert insights, "The Data-Driven Doctor" explores the latest advancements in AI technology and their profound implications for the practice of medicine. Whether you're a healthcare professional seeking to stay ahead of the curve, a patient curious about the future of healthcare, or an AI enthusiast eager to learn about its transformative potential, this book is your indispensable guide to navigating the dynamic intersection of AI and medicine. Discover how AI-driven diagnostic tools are revolutionizing disease detection, how personalized medicine is transforming treatment paradigms, and how AI-powered clinical decision support systems are empowering healthcare providers to deliver more precise, patient-centered care than ever before. Explore the ethical, social, and regulatory considerations surrounding AI use in medicine, and gain valuable insights into the future of healthcare delivery in the digital age. Packed with fascinating anecdotes, thought-provoking insights, and actionable takeaways, "The Data-Driven Doctor" is a must-read for anyone passionate about the future of healthcare and the transformative potential of AI. Whether you're a seasoned healthcare professional, a curious patient, or an AI enthusiast, this book will inspire and inform, guiding you on an enlightening journey into the future of medicine. Don't miss out on your chance to explore the future of healthcare with "The Data-Driven Doctor." Order your copy today and join the revolution in AI-driven medicine!

Download or read book Data Driven Approaches for Healthcare written by Chengliang Yang and published by CRC Press. This book was released on 2019-10-01 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients’ acute and chronic condition loads and demographic characteristics

Download or read book Medical Data Analysis and Processing using Explainable Artificial Intelligence written by Om Prakash Jena and published by CRC Press. This book was released on 2023-11-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical. Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science. Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications. Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data. Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing. Discusses machine learning and deep learning scalability models in healthcare systems. This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.

Download or read book Artificial Intelligence for the Internet of Health Things written by K. Shankar and published by CRC Press. This book was released on 2021-05-10 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.

Download or read book Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging written by Kenji Suzuki and published by Springer. This book was released on 2018-01-09 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.

Download or read book Medical Diagnosis Using Artificial Neural Networks written by Moein, Sara and published by IGI Global. This book was released on 2014-06-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced conceptual modeling techniques serve as a powerful tool for those in the medical field by increasing the accuracy and efficiency of the diagnostic process. The application of artificial intelligence assists medical professionals to analyze and comprehend a broad range of medical data, thus eliminating the potential for human error. Medical Diagnosis Using Artificial Neural Networks introduces effective parameters for improving the performance and application of machine learning and pattern recognition techniques to facilitate medical processes. This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between artificial intelligence and medical science through the use of informatics to improve the quality of medical care.

Download or read book Driving Smart Medical Diagnosis Through AI Powered Technologies and Applications written by Khang, Alex and published by IGI Global. This book was released on 2024-02-26 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Academic scholars face the daunting challenge of keeping pace with the rapid evolution of innovative technologies. The emergence of AI-driven solutions, deep learning frameworks, and medical robotics introduces a complex terrain, demanding in-depth understanding and analysis. As scholars navigate the intricacies of patient hate speech detection, cardiovascular diseases AI-CDSS, and the revolution in medical diagnostics, a pressing need arises for comprehensive insights that bridge the gap between theoretical knowledge and practical applications. Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications serves as a solution in this era of transformative healthcare and addresses these challenges head-on. It unravels the complexities surrounding the implementation of AI in healthcare, offering in-depth discussions on the latest breakthroughs. From unraveling the mysteries of AI-driven cataract detection to exploring the implications of decentralized mammography classification, the book is a valuable resource that equips scholars with the knowledge to navigate this innovative landscape.

Download or read book Smart Systems for Industrial Applications written by C. Venkatesh and published by John Wiley & Sons. This book was released on 2022-01-07 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: SMART SYSTEMS FOR INDUSTRIAL APPLICATIONS The prime objective of this book is to provide an insight into the role and advancements of artificial intelligence in electrical systems and future challenges. The book covers a broad range of topics about AI from a multidisciplinary point of view, starting with its history and continuing on to theories about artificial vs. human intelligence, concepts, and regulations concerning AI, human-machine distribution of power and control, delegation of decisions, the social and economic impact of AI, etc. The prominent role that AI plays in society by connecting people through technologies is highlighted in this book. It also covers key aspects of various AI applications in electrical systems in order to enable growth in electrical engineering. The impact that AI has on social and economic factors is also examined from various perspectives. Moreover, many intriguing aspects of AI techniques in different domains are covered such as e-learning, healthcare, smart grid, virtual assistance, etc. Audience The book will be of interest to researchers and postgraduate students in artificial intelligence, electrical and electronic engineering, as well as those engineers working in the application areas such as healthcare, energy systems, education, and others.

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Download or read book Reinventing Clinical Decision Support written by Paul Cerrato and published by Taylor & Francis. This book was released on 2020-01-06 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Download or read book Deep Learning for Medical Applications with Unique Data written by Deepak Gupta and published by Academic Press. This book was released on 2022-02-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems. Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications

Download or read book Precision Medicine and Artificial Intelligence written by Michael Mahler and published by Academic Press. This book was released on 2021-03-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine

Download or read book Medical Imaging written by K.C. Santosh and published by CRC Press. This book was released on 2019-08-20 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.