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Titlebook: Artificial Intelligence and Healthcare; The Impact of Algori Natasha H. Williams Book 2023 The Editor(s) (if applicable) and The Author(s),

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發(fā)表于 2025-3-21 18:16:40 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Artificial Intelligence and Healthcare
期刊簡稱The Impact of Algori
影響因子2023Natasha H. Williams
視頻videohttp://file.papertrans.cn/163/162210/162210.mp4
發(fā)行地址Covers ethics, artificial intelligence, and health disparities.Shows how AI may increase—instead of decrease—health disparities.Is of interest to a broad audience, including health services researcher
學科分類The International Library of Bioethics
圖書封面Titlebook: Artificial Intelligence and Healthcare; The Impact of Algori Natasha H. Williams Book 2023 The Editor(s) (if applicable) and The Author(s),
影響因子.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..
Pindex Book 2023
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The Inclusion of Racial and Ethnic Minority Groups in Clinical Trials,ent, protocol, or device. The participation of racial and ethnic minority groups in clinical trials research is crucial to ensure data quality and generalizability. Most clinical trials lack adequate participation of racial and ethnic minority groups. One reason is mistrust due to a history of scien
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2662-9186 st to a broad audience, including health services researcher.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 det
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https://doi.org/10.1007/978-3-658-45853-9 treatment outcomes, and decrease patient mortality. To achieve these ambitious goals, AI depends upon massive streams of data from various sources. Section?. defines AI. Section?. describes data. Section?. explores data and algorithmic bias. Section?. discusses race-based algorithms. Section?. summarizes key points in the chapter.
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