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Approaches to human-centered AI in h...

Balusamy, Balamurugan.

Approaches to human-centered AI in healthcare

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Approaches to human-centered AI in healthcareVeena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanova, editors.
其他題名:	Approaches to human-centered artificial intelligence in healthcare
其他作者:	Grover, Veena,
出版者:	Hershey, Pennsylvania :IGI Global,2024.
面頁冊數:	1 online resource (328 p.)
標題:	Patient-centered health care.
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2238-3
ISBN:	9798369322390$q(ebook)

Approaches to human-centered AI in healthcare
Approaches to human-centered AI in healthcare[electronic resource] /Approaches to human-centered artificial intelligence in healthcareVeena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanova, editors. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (328 p.)

Includes bibliographical references and index.

Chapter 1. Patient-centric AI: advancing healthcare through human-centered innovation -- Chapter 2. Virtual insights, real solutions: the promise of augmented reality in medicine -- Chapter 3. An in-depth exploration of AI and humanoid robotics' role in contemporary healthcare -- Chapter 4. Revolutionizing drug discovery with artificial intelligence: enhancing efficiency, addressing ethical concerns, and overcoming limitations -- Chapter 5. Applications of AI in drug discovery: its challenges, opportunities, and strategies -- Chapter 6. Artificial intelligence in medical imaging by machine learning and deep learning -- Chapter 7. Comparative assessment of machine learning methods for early prediction ofdiseases using health indicators -- Chapter 8. Comparative analysis of machine learning approaches for antimicrobial peptide prediction: a comprehensive review -- Chapter 9. A deep learning-based malarial parasite detection using blood smear images for healthcare techniques -- Chapter 10. Deep learning-based voice pathology detection from electroglottography -- Chapter 11. COVID-19 pandemic's personal safety is revolutionized by the smart mask.

"The integration of artificial intelligence (AI) stands as both a promise and a challenge in the field of healthcare. As technological advancements reshape the industry, academic scholars find themselves at the forefront of a crucial dialogue about the ethical implications and societal repercussions of AI. The accelerating sophistication of AI technologies brings forth a central dilemma: how to maintain the crucial human touch required for compassionate and effective patient care in the face of unprecedented technical progress. This challenge is not only a theoretical concern but a pressing reality as healthcare systems increasingly rely on AI-driven solutions.Approaches to Human-Centered AI in Healthcare emerges as a significant guide, offering a comprehensive exploration of the opportunities and challenges entwined with the integration of AI into healthcare. The book becomes a critical compass, navigating readers through the intricate intersections of AI and patient care. By delving into real-world case studies, cutting-edge research findings, and practical recommendations, it provides a roadmap for scholars to navigate the complexities of healthcare AI. In doing so, it aims not only to inform but to shape the discourse around the responsible integration of AI, ensuring that the fundamental principles of compassionate patient care remain at the forefront."--

ISBN: 9798369322390$q(ebook)Subjects--Topical Terms:

678721
Patient-centered health care.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: RA971.6 / .A67 2024e

Dewey Class. No.: 362.10285

National Library of Medicine Call No.: W 84.7 / .A67 2024e

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505 0 $a Chapter 1. Patient-centric AI: advancing healthcare through human-centered innovation -- Chapter 2. Virtual insights, real solutions: the promise of augmented reality in medicine -- Chapter 3. An in-depth exploration of AI and humanoid robotics' role in contemporary healthcare -- Chapter 4. Revolutionizing drug discovery with artificial intelligence: enhancing efficiency, addressing ethical concerns, and overcoming limitations -- Chapter 5. Applications of AI in drug discovery: its challenges, opportunities, and strategies -- Chapter 6. Artificial intelligence in medical imaging by machine learning and deep learning -- Chapter 7. Comparative assessment of machine learning methods for early prediction ofdiseases using health indicators -- Chapter 8. Comparative analysis of machine learning approaches for antimicrobial peptide prediction: a comprehensive review -- Chapter 9. A deep learning-based malarial parasite detection using blood smear images for healthcare techniques -- Chapter 10. Deep learning-based voice pathology detection from electroglottography -- Chapter 11. COVID-19 pandemic's personal safety is revolutionized by the smart mask.
520 3 $a "The integration of artificial intelligence (AI) stands as both a promise and a challenge in the field of healthcare. As technological advancements reshape the industry, academic scholars find themselves at the forefront of a crucial dialogue about the ethical implications and societal repercussions of AI. The accelerating sophistication of AI technologies brings forth a central dilemma: how to maintain the crucial human touch required for compassionate and effective patient care in the face of unprecedented technical progress. This challenge is not only a theoretical concern but a pressing reality as healthcare systems increasingly rely on AI-driven solutions.Approaches to Human-Centered AI in Healthcare emerges as a significant guide, offering a comprehensive exploration of the opportunities and challenges entwined with the integration of AI into healthcare. The book becomes a critical compass, navigating readers through the intricate intersections of AI and patient care. By delving into real-world case studies, cutting-edge research findings, and practical recommendations, it provides a roadmap for scholars to navigate the complexities of healthcare AI. In doing so, it aims not only to inform but to shape the discourse around the responsible integration of AI, ensuring that the fundamental principles of compassionate patient care remain at the forefront."-- $c Provided by publisher.
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