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

被引:2
作者
Bhuyan, Soumitra S. [1 ]
Sateesh, Vidyoth [1 ]
Mukul, Naya [2 ]
Galvankar, Alay [3 ]
Mahmood, Asos [4 ]
Nauman, Muhammad [5 ]
Rai, Akash [1 ]
Bordoloi, Kahuwa [6 ]
Basu, Urmi [7 ]
Samuel, Jim [1 ]
机构
[1] Rutgers State Univ, Edward J Bloustein Sch Planning & Publ Policy, 255 Civ Sq Bldg 33 Livingston Ave 400, New Brunswick, NJ 08901 USA
[2] RICE UNIV, Sch Social Policy, HOUSTON, TX USA
[3] Biotechnol High Sch, Freehold, NJ USA
[4] Univ Tennessee, Coll Med, Hlth Sci Ctr, Ctr Hlth Syst Improvement, Memphis, TN USA
[5] Univ Engn & Technol, Peshawar, Pakistan
[6] St Josephs Univ, Dept Psychol & Counselling, Bangalore, India
[7] Insight Biopharm, Princeton, NJ USA
关键词
Generative AI; Artificial intelligence; Healthcare; Large language models; Clinical excellence; Ethics; Health information technology; AI applications; ChatGPT; Medicine; PERFORMANCE;
D O I
10.1007/s10916-024-02136-1
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
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页数:11
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