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Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency.

作者信息

Bhuyan Soumitra S, Sateesh Vidyoth, Mukul Naya, Galvankar Alay, Mahmood Asos, Nauman Muhammad, Rai Akash, Bordoloi Kahuwa, Basu Urmi, Samuel Jim

机构信息

Edward J. Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 255, Civic Square Building 33 Livingston Ave #400, New Brunswick, NJ, 08901, USA.

School of Social Policy, Rice University, Houston, TX, USA.

出版信息

J Med Syst. 2025 Jan 16;49(1):10. doi: 10.1007/s10916-024-02136-1.


DOI:10.1007/s10916-024-02136-1
PMID:39820845
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11739231/
Abstract

Generative Artificial Intelligence (Gen AI) has transformative potential in healthcare to enhance patient care, personalize treatment options, train healthcare professionals, and advance medical research. This paper examines various clinical and non-clinical applications of Gen AI. In clinical settings, Gen AI supports the creation of customized treatment plans, generation of synthetic data, analysis of medical images, nursing workflow management, risk prediction, pandemic preparedness, and population health management. By automating administrative tasks such as medical documentations, Gen AI has the potential to reduce clinician burnout, freeing more time for direct patient care. Furthermore, application of Gen AI may enhance surgical outcomes by providing real-time feedback and automation of certain tasks in operating rooms. The generation of synthetic data opens new avenues for model training for diseases and simulation, enhancing research capabilities and improving predictive accuracy. In non-clinical contexts, Gen AI improves medical education, public relations, revenue cycle management, healthcare marketing etc. Its capacity for continuous learning and adaptation enables it to drive ongoing improvements in clinical and operational efficiencies, making healthcare delivery more proactive, predictive, and precise.

摘要

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Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency.

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[Medical education and artificial intelligence: perspectives and ethical challenges].

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[2]
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[3]
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[4]
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[5]
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[7]
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本文引用的文献

[1]
Retained ventriculoperitoneal shunt and brain granuloma.

J Formos Med Assoc. 2025-6

[2]
Foundation Models, Generative AI, and Large Language Models: Essentials for Nursing.

Comput Inform Nurs. 2024-5-1

[3]
The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century.

Bioengineering (Basel). 2024-3-29

[4]
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Surgery. 2024-6

[5]
Artificial Intelligence-Generated Draft Replies to Patient Inbox Messages.

JAMA Netw Open. 2024-3-4

[6]
Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.

Implement Sci. 2024-3-15

[7]
Exploring generative AI's role in alleviating nursing workload and burnout in Taiwan.

J Formos Med Assoc. 2024-7

[8]
The ChatGPT effect and transforming nursing education with generative AI: Discussion paper.

Nurse Educ Pract. 2024-2

[9]
AI-powered real-time annotations during urologic surgery: The future of training and quality metrics.

Urol Oncol. 2024-3

[10]
Prompt engineering when using generative AI in nursing education.

Nurse Educ Pract. 2024-1

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