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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 and Machine Learning in Emergency Medicine

Artificial Intelligence and Machine Learning in Emergency Medicine
Author: Century writer
Publisher:
Total Pages: 44
Release: 2021-04-07
Genre:
ISBN:
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Emergency Medicine (EM) is a growing specialty and plays a critical role in society for receiving patients in need of urgentmedical attention. These patients often present with a myriad of presenting complaints. In the US, there were 137 million Emergency Department (ED) visits in 2015, account- ing for almost 14% of all hospital visits [1]. Multiple concerns have been brought up by patients. For example, long waiting times is one of the known factors contributing to decreased patient satisfaction in the ED [2,3]. In the UK, one study has shown that the median waiting time for decision making in the ED between April 2008 and April 2013 was almost 3 h, with up to 10% having wait times of more than 4 h [4]. Along with other factors, another study has shown that this had led to as much as 7.4% of patients leaving the ED without receiving treatment [5]. Recent advancements in technology has brought into the field a suite of tools, with great potential of improving processes and overall quality of healthcare in EM. With further evidence presented, it is believed that AI can seek to improve patient experiences in the ED. In this Book , we aim to study the evidence to support the potential of AI in EM.

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

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.

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 Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert
Publisher: Springer
Total Pages: 373
Release: 2019-01-29
Genre: Medical
ISBN: 3319948784
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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.

Computational Intelligence and Soft Computing Applications in Healthcare Management Science

Computational Intelligence and Soft Computing Applications in Healthcare Management Science
Author: Gul, Muhammet
Publisher: IGI Global
Total Pages: 322
Release: 2020-03-06
Genre: Medical
ISBN: 1799825825
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In today’s modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.