Applications of Artificial Intelligence in Medicine Practice by
This book focuses on a variety of interdisciplinary perspectives concerning the theory and application of artificial intelligence (AI) in medicine, medically oriented human biology, and healthcare. The list of topics includes the application of AI in biomedicine and clinical medicine, machine learning-based decision support, robotic surgery, data analytics and mining, laboratory information systems, and usage of AI in medical education. Special attention is given to the practical aspect of a study. Hence, the inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly highlighted.
Artificial Intelligence in Medicine and Surgery by
Human history is filled with inventions and other innovations that resulted in a significant and lasting change in our civilization's course of development. From gasoline-powered vehicles to transistor-based electronics or jet airplanes, things we now take for granted often appeared suddenly and unexpectedly. Yet after their introduction, our world changed forever. Over the past two decades, artificial intelligence (AI) and machine learning (ML) have been stealthily increasing their presence in our everyday lives. This "randomly systematic" adoption process is exposing humanity to something we never previously directly faced: an intelligence that may (and likely will) exceed our own. Despite this, most people are not fully aware of current (and future) benefits, limitations, and threats related to AI/ML. Within health care, there is little awareness of what AI/ML is capable of and how these new capabilities are being implemented or utilized. It is this current state that serves as our "starting point" in the emerging debate on AI/ML in medicine and surgery, including its integration, projected influence, and many other considerations that are not that different from other past technology adoption paradigms. This book discusses both current trends and future developments in AI and ML across health care.
Explainable Artificial Intelligence in Stroke from the Clinical, Rehabilitation and Nursing Perspectives by
As we know, strokes are one of the world's leading causes of death, and the cruel aspect of a stroke is that it leaves people with severe functional disability and/or cognitive impairment. Strokes have a significant impact on economies worldwide, as it is estimated that about 10% of the male population and 8% of the female population are affected by them. Such people need personal help in their everyday life and must be materially supported by social services. With the advancement of medicine, artificial intelligence, and new technologies have been developing rapidly and are gradually applied in diseases of the nervous system, increasingly helping diagnosis, treatment, rehabilitation, and prognosis of disease.This Special Issue has collected the 14 papers on artificial intelligence and new technologies in strokes, including in the aspects of diagnosis, treatment, prognosis, rehabilitation, and nursing.
Artificial Intelligence and Machine Learning in Health Care and Medical Sciences by
This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfallsis a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.
The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We? by
This book is a reprint of the Special Issue entitled "The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?". Artificial intelligence is extending into the world of both digital radiology and digital pathology, and involves many scholars in the areas of biomedicine, technology, and bioethics. There is a particular need for scholars to focus on both the innovations in this field and the problems hampering integration into a robust and effective process in stable health care models in the health domain. Many professionals involved in these fields of digital health were encouraged to contribute with their experiences. This book contains contributions from various experts across different fields. Aspects of the integration in the health domain have been faced. Particular space was dedicated to overviewing the challenges, opportunities, and problems in both radiology and pathology. Clinal deepens are available in cardiology, the hystopathology of breast cancer, and colonoscopy. Dedicated studies were based on surveys which investigated students and insiders, opinions, attitudes, and self-perception on the integration of artificial intelligence in this field.