Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’
The rapid development of specific-purpose Large Language Models (LLMs), such as Med-PaLM, MEDITRON-70B, and Med-Gemini, has significantly impacted healthcare, offering unprecedented capabilities in clinical decision support, diagnostics, and personalized health monitoring. This paper reviews the adv...
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/1999-5903/16/12/462 |
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| author | Peng Zhang Jiayu Shi Maged N. Kamel Boulos |
| author_facet | Peng Zhang Jiayu Shi Maged N. Kamel Boulos |
| author_sort | Peng Zhang |
| collection | DOAJ |
| description | The rapid development of specific-purpose Large Language Models (LLMs), such as Med-PaLM, MEDITRON-70B, and Med-Gemini, has significantly impacted healthcare, offering unprecedented capabilities in clinical decision support, diagnostics, and personalized health monitoring. This paper reviews the advancements in medicine-specific LLMs, the integration of Retrieval-Augmented Generation (RAG) and prompt engineering, and their applications in improving diagnostic accuracy and educational utility. Despite the potential, these technologies present challenges, including bias, hallucinations, and the need for robust safety protocols. The paper also discusses the regulatory and ethical considerations necessary for integrating these models into mainstream healthcare. By examining current studies and developments, this paper aims to provide a comprehensive overview of the state of LLMs in medicine and highlight the future directions for research and application. The study concludes that while LLMs hold immense potential, their safe and effective integration into clinical practice requires rigorous testing, ongoing evaluation, and continuous collaboration among stakeholders. |
| format | Article |
| id | doaj-art-becdea0cef414770a363e42198c5be3d |
| institution | DOAJ |
| issn | 1999-5903 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj-art-becdea0cef414770a363e42198c5be3d2025-08-20T02:53:30ZengMDPI AGFuture Internet1999-59032024-12-01161246210.3390/fi16120462Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’Peng Zhang0Jiayu Shi1Maged N. Kamel Boulos2Department of Computer Science and Data Science Institute, Vanderbilt University, Nashville, TN 37240, USADepartment of Computer Science and Data Science Institute, Vanderbilt University, Nashville, TN 37240, USASchool of Medicine, University of Lisbon, 1649-028 Lisbon, PortugalThe rapid development of specific-purpose Large Language Models (LLMs), such as Med-PaLM, MEDITRON-70B, and Med-Gemini, has significantly impacted healthcare, offering unprecedented capabilities in clinical decision support, diagnostics, and personalized health monitoring. This paper reviews the advancements in medicine-specific LLMs, the integration of Retrieval-Augmented Generation (RAG) and prompt engineering, and their applications in improving diagnostic accuracy and educational utility. Despite the potential, these technologies present challenges, including bias, hallucinations, and the need for robust safety protocols. The paper also discusses the regulatory and ethical considerations necessary for integrating these models into mainstream healthcare. By examining current studies and developments, this paper aims to provide a comprehensive overview of the state of LLMs in medicine and highlight the future directions for research and application. The study concludes that while LLMs hold immense potential, their safe and effective integration into clinical practice requires rigorous testing, ongoing evaluation, and continuous collaboration among stakeholders.https://www.mdpi.com/1999-5903/16/12/462generative AIlarge language modelsAI chatbotsChatGPTartificial intelligenceretrieval-augmented generation |
| spellingShingle | Peng Zhang Jiayu Shi Maged N. Kamel Boulos Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ Future Internet generative AI large language models AI chatbots ChatGPT artificial intelligence retrieval-augmented generation |
| title | Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ |
| title_full | Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ |
| title_fullStr | Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ |
| title_full_unstemmed | Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ |
| title_short | Generative AI in Medicine and Healthcare: Moving Beyond the ‘Peak of Inflated Expectations’ |
| title_sort | generative ai in medicine and healthcare moving beyond the peak of inflated expectations |
| topic | generative AI large language models AI chatbots ChatGPT artificial intelligence retrieval-augmented generation |
| url | https://www.mdpi.com/1999-5903/16/12/462 |
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