Applications of Large Language Models (LLM) in Healthcare Systems: Opportunities, Challenges, and Ethical Considerations
暫譯: 大型語言模型（LLM）在醫療系統中的應用：機會、挑戰與倫理考量

Zamanifar, Azadeh, Faezipour, Miad, Soleimanian Gharehchopogh, Farhad

Applications of Large Language Models (LLM) in Healthcare Systems: Opportunities, Challenges, and Ethical Considerations
  • 出版商: CRC
  • 出版日期: 2025-11-11
  • 售價: $5,520
  • 貴賓價: 9.5 折 $5,244
  • 語言: 英文
  • 頁數: 292
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1041124910
  • ISBN-13: 9781041124917
  • 相關分類: Large language model

    • 海外代購書籍(需單獨結帳)

商品描述

This book offers a comprehensive exploration into the role of Large Language Models (LLMs) in modern healthcare. It focuses specifically on the lifecycle of LLM deployment in healthcare settings, including transparency, accountability, data privacy, and regulatory compliance to ensure safe and effective use.

By bridging the gap between technical artificial intelligence (AI) development and clinical application, this book highlights the critical collaboration between clinicians and data scientists to create representative datasets and fine-tune models for clinical accuracy and interpretability. Real-world challenges such as mitigating bias, managing AI hallucinations, and safeguarding patient confidentiality are explored, alongside strategies for continuous improvement and long-term impact assessment.

Key features include:

- Case studies illustrating LLM applications in clinical decision support, medical imaging, patient communication, and administrative automation.

- In-depth discussion of data privacy, regulatory compliance, and ethical considerations in AI healthcare applications.

- Insights into overcoming challenges like bias, hallucinations, and interoperability with existing health information systems.

- How LLMs could revolutionize patient care in future, including operational efficiency and personalized medicine.

This book is an essential resource for clinicians, healthcare executives, technologists, data scientists, and students seeking to harness the power of LLMs to improve patient outcomes and streamline healthcare delivery.

商品描述(中文翻譯)

這本書全面探討大型語言模型（Large Language Models, LLMs）在現代醫療保健中的角色。它特別關注LLM在醫療環境中的部署生命周期，包括透明度、問責制、數據隱私和法規遵從，以確保安全和有效的使用。

通過彌合技術人工智慧（AI）開發與臨床應用之間的鴻溝，本書強調臨床醫生與數據科學家之間的關鍵合作，以創建具有代表性的數據集並微調模型，以達到臨床準確性和可解釋性。書中探討了減少偏見、管理AI幻覺和保護病人隱私等現實挑戰，以及持續改進和長期影響評估的策略。

主要特色包括：
- 案例研究，說明LLM在臨床決策支持、醫學影像、病人溝通和行政自動化中的應用。
- 深入討論數據隱私、法規遵從和AI醫療應用中的倫理考量。
- 對克服偏見、幻覺和與現有健康信息系統互操作性等挑戰的見解。
- LLM如何在未來徹底改變病人護理，包括運營效率和個性化醫療。

這本書是臨床醫生、醫療高管、技術專家、數據科學家和希望利用LLM的力量來改善病人結果和簡化醫療服務的學生的重要資源。

作者簡介

Azadeh Zamanifar is currently head of computer engineering department at Islamic Azad university, science and research branch. She received her B.Sc. degree in Computer Engineering (Hardware) from Tehran University in 2002. She went on to complete her M.Sc. degree in Computer Engineering (Software) at the University of Science and Technology in 2008, before obtaining her Ph.D. in Software Engineering from Shahid Beheshti University in Tehran, Iran. Currently, she serves as the Head of the Software and AI Department at Islamic Azad University Science and Research Branch. Her research interests include health care systems, Machine Learning and distributed systems.

Miad Faezipour is an associate professor of electrical and computer engineering technology at the School of Engineering Technology, Purdue University. She is also a full member of the Regenstrief Center for Healthcare Engineering (RCHE) and a core faculty member of the Applied AI Research Center (AARC) at Purdue University. She is the founder and director of the Digital/Biomedical Embedded Systems and Technology (D-BEST) research laboratory. She received the M.Sc. and Ph.D. degrees in electrical engineering from the University of Texas at Dallas. Prior to joining Purdue University in August 2021, she has served the Computer Science & Engineering and Biomedical Engineering programs of the University of Bridgeport, CT as a faculty member for ten years. Her research interests primarily include healthcare technology, digital/biomedical embedded hardware/software co-designs, biomedical signal/image processing, computer vision, healthcare/biomedical informatics, artificial intelligence and AI-based bio-data augmentation. She is a Senior Member of IEEE, EMBS and the IEEE Women in Engineering.

Farhad Soleimanian Gharehchopogh: Department of computer engineering, Urmia branch, Islamic Azad university, Urmia, Iran, Farhad Soleimanian Gharehchopogh an Associate Professor in the Department of Computer Engineering at Urmia Branch, Islamic Azad University, since 2015, brings a wealth of experience to his role. He received a B.S. from the Shabestar Branch, Islamic Azad University in 2002, and an M.S. from Cukurova University in Adana, Turkey. He earned his Ph.D. in Computer Engineering from Hacettepe University in 2015. Dr Farhad has published over 200 journal articles, many in high-impact journals, with over 9000 citations. His research interests span Data Mining and Machine Learning. Much of his work has been on improving the understanding, design, and performance of algorithms, mainly through the application of engineering.

Amirfarhad Farhadi holds a Ph.D. in Artificial Intelligence and is currently a Postdoctoral Fellow at Iran University of Science and Technology. He also serves as an Adjunct Professor in the Department of Computer Engineering at the Science and Research Branch of Islamic Azad University. His research expertise spans Artificial Intelligence (AI), machine learning, deep learning, transfer learning, reinforcement learning, natural language processing (NLP), and healthcare systems. Dr. Farhadi serves as a reviewer for esteemed journals, including IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Neural Networks and Learning Systems, among others. In addition to his academic contributions, he holds patents in robotics and actively participates in the AI industry, focusing on innovative applications and technological advancements.

作者簡介(中文翻譯)

Azadeh Zamanifar 目前是伊斯蘭阿茲哈大學科學與研究分校計算機工程系的系主任。她於2002年在德黑蘭大學獲得計算機工程（硬體）學士學位，並於2008年在科學與技術大學完成計算機工程（軟體）碩士學位，隨後在伊朗德黑蘭的沙希德·貝赫什提大學獲得軟體工程博士學位。目前，她擔任伊斯蘭阿茲哈大學科學與研究分校軟體與人工智慧系的系主任。她的研究興趣包括健康照護系統、機器學習和分散式系統。

Miad Faezipour 是普渡大學工程技術學院的電氣與計算機工程技術副教授。她同時也是Regenstrief健康工程中心（RCHE）的正式成員，以及普渡大學應用人工智慧研究中心（AARC）的核心教職成員。她是數位/生醫嵌入式系統與技術（D-BEST）研究實驗室的創始人和主任。她在德克薩斯州達拉斯大學獲得電氣工程碩士和博士學位。在2021年8月加入普渡大學之前，她在康乃狄克州布里奇波特大學的計算機科學與工程及生醫工程項目擔任教職十年。她的研究興趣主要包括健康科技、數位/生醫嵌入式硬體/軟體共同設計、生醫信號/影像處理、計算機視覺、健康/生醫資訊學、人工智慧及基於AI的生物數據增強。她是IEEE、EMBS及IEEE女性工程師的資深會員。

Farhad Soleimanian Gharehchopogh 是伊斯蘭阿茲哈大學烏爾米亞分校計算機工程系的副教授，自2015年以來在此任教，擁有豐富的經驗。他於2002年在伊斯蘭阿茲哈大學沙巴斯塔爾分校獲得學士學位，並在土耳其阿達納的Cukurova大學獲得碩士學位。他於2015年在哈哲特佩大學獲得計算機工程博士學位。Farhad博士已發表超過200篇期刊文章，許多發表在高影響力的期刊上，引用次數超過9000次。他的研究興趣涵蓋數據挖掘和機器學習。他的許多工作集中在通過工程應用來改善算法的理解、設計和性能。

Amirfarhad Farhadi 擁有人工智慧博士學位，目前是伊朗科學與技術大學的博士後研究員。他同時擔任伊斯蘭阿茲哈大學科學與研究分校計算機工程系的兼任教授。他的研究專長涵蓋人工智慧（AI）、機器學習、深度學習、遷移學習、強化學習、自然語言處理（NLP）和健康照護系統。Farhadi博士擔任多本知名期刊的審稿人，包括IEEE模式分析與機器智慧期刊（TPAMI）和IEEE神經網絡與學習系統期刊等。除了學術貢獻外，他在機器人技術方面擁有專利，並積極參與AI產業，專注於創新應用和技術進步。

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