Clinical Application Of Artificial Intelligence In Emergency And Critical Care Medicine Volume Iv PDF Download

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Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume IV

Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume IV
Author: Zhongheng Zhang
Publisher: Frontiers Media SA
Total Pages: 192
Release: 2024-01-23
Genre: Medical
ISBN: 2832543375
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This Research Topic is the fourth volume of the series Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine Volume I: Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume I Volume II:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume II Volume III:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume III Analytics based on artificial intelligence has greatly advanced scientific research fields like natural language processing and imaging classification. Clinical research has also greatly benefited from artificial intelligence. Emergency and critical care physicians face patients with rapidly changing conditions, which require accurate risk stratification and initiation of rescue therapy. Furthermore, critically ill patients, such as those with sepsis, acute respiratory distress syndrome, and trauma, are comprised of heterogeneous population. The “one-size-fit-all” paradigm may not fit for the management of such heterogeneous patient population. Thus, artificial intelligence can be employed to identify novel subphenotypes of these patients. These sub classifications can provide not only prognostic value for risk stratification but also predictive value for individualized treatment. With the development of transcriptome providing a large amount of information for an individual, artificial intelligence can greatly help to identify useful information from high dimensional data. Altogether, it is of great importance to further utilize artificial intelligence in the management of critically ill patients.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Total Pages: 385
Release: 2020-06-21
Genre: Computers
ISBN: 0128184396
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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

Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine

Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine
Author: Zhongheng Zhang
Publisher:
Total Pages: 0
Release: 2024-04-30
Genre: Medical
ISBN: 9783725809097
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Critical illness refers to severe diseases or conditions where health status changes rapidly and may pose an immediate threat to life within a short period of time. The key to successful treatment of critically ill patients involves various aspects of diagnosis, including early prediction of adverse events, accurate identification of pathogens, and differential diagnosis of symptoms. Critically ill patients typically generate vast amounts of data from medical equipment such as bedside monitors, ventilators, and renal replacement therapy devices. Handling such large volumes of data is challenging for human intuition alone. Artificial intelligence can learn complex data structures to acquire knowledge and insights, thereby profoundly impacting the management of critically ill patients. In this context, we have organized this Special Issue to explore the application of artificial intelligence in the management of major diseases, aiming to significantly advance future healthcare. In this Special Issue, researchers from various countries and regions have explored the application of artificial intelligence in critical care, covering aspects such as diagnosis, management, and prognosis. Overall, these studies elucidate the transformative impact of artificial intelligence and machine learning on medical diagnosis and prognosis, heralding a new era of precision medicine that holds promise for improving patient outcomes and optimizing healthcare services.

Emergency Medicine: Applications of Artificial Intelligence

Emergency Medicine: Applications of Artificial Intelligence
Author: Sonja Andersen
Publisher: American Medical Publishers
Total Pages: 0
Release: 2023-09-26
Genre: Medical
ISBN:
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The rapid advancements in artificial intelligence technology have paved the way for the use of machine learning applications in health care. These applications address existing challenges in the emergency department such as triage and disposition, early detection of conditions and outcomes, emergency department operations, and therapeutic interventions. Artificial intelligence can be used in three ways in the context of emergency and critical care. The first one is to build risk stratification prediction models in critical care. The second use of AI involves utilizing unsupervised machine learning techniques to divide the varied population into homogeneous subgroups. The third use of AI is for reinforcement learning algorithms to prescribe treatment regimens in a sequential way. The dynamic treatment regime (DTR) model uses reinforcement learning to estimate a set of decision rules, one for each step of intervention. It specifies how to tailor treatments to patients considering their treatment and covariate histories. DTR lowers model complexity and is considered more appropriate for medical epidemiology. This book is a vital tool for all researching or studying the role of AI in emergency medicine. It aims to equip students and experts with the advanced topics and upcoming concepts in this subject.

Artificial Intelligence in Healthcare and Medicine

Artificial Intelligence in Healthcare and Medicine
Author: Kayvan Najarian
Publisher: CRC Press
Total Pages: 300
Release: 2022-04-06
Genre: Computers
ISBN: 1000565815
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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.

AI in Clinical Medicine

AI in Clinical Medicine
Author: Michael F. Byrne
Publisher: John Wiley & Sons
Total Pages: 597
Release: 2023-05-01
Genre: Medical
ISBN: 1119790646
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AI IN CLINICAL MEDICINE An essential overview of the application of artificial intelligence in clinical medicine AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future. Readers will find that this book: Describes where AI is currently being used to change practice, and provides successful cases of AI approaches in specific medical domains. Dives into the actual implementation of AI in the healthcare setting, and addresses reimbursement, workforce, and many other practical issues. Addresses some of the unique challenges associated with AI in clinical medicine including ethical issues, as well as regulatory and privacy concerns. Includes bulleted lists of learning objectives, key insights, clinical vignettes, brief examples of where AI is successfully deployed, and examples of potential problematic uses of AI and possible risks. From radiology, to pathology, dermatology, endoscopy, robotics, virtual reality, and more, AI in Clinical Medicine: A Practical Guide for Healthcare Professionals explores all recent state-of-the-art developments in the field. It is an essential resource for a general medical audience across all disciplines, from students to clinicians, academics to policy makers.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing
Publisher: Academic Press
Total Pages: 570
Release: 2020-09-03
Genre: Medical
ISBN: 0128212586
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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