Affiliation:
1. Warren Alpert Medical School, Brown University, East Providence, RI 02914, USA
2. Department of Orthopedics, Warren Alpert Medical School, Brown University, Providence, RI 02912, USA
Abstract
Large Language Models (LLMs have the potential to revolutionize clinical medicine by enhancing healthcare access, diagnosis, surgical planning, and education. However, their utilization requires careful, prompt engineering to mitigate challenges like hallucinations and biases. Proper utilization of LLMs involves understanding foundational concepts such as tokenization, embeddings, and attention mechanisms, alongside strategic prompting techniques to ensure accurate outputs. For innovative healthcare solutions, it is essential to maintain ongoing collaboration between AI technology and medical professionals. Ethical considerations, including data security and bias mitigation, are critical to their application. By leveraging LLMs as supplementary resources in research and education, we can enhance learning and support knowledge-based inquiries, ultimately advancing the quality and accessibility of medical care. Continued research and development are necessary to fully realize the potential of LLMs in transforming healthcare.
Reference47 articles.
1. Yu, P., Xu, H., Hu, X., and Deng, C. (2023). Leveraging Generative AI and Large Language Models: A Comprehensive Roadmap for Healthcare Integration. Healthcare, 11.
2. Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., and Iwasawa, Y. (2023). Large Language Models Are Ze-ro-Shot Reasoners. arXiv.
3. ChatGPT and Large Language Models in Orthopedics: From Education and Surgery to Research;Chatterjee;J. Exp. Orthop.,2023
4. Harnessing the Power of Large Language Models (LLMs) for Electronic Health Records (EHRs) Optimization;Nashwan;Cureus,2023
5. Developing Prompts from Large Language Model for Extracting Clinical Information from Pathology and Ultrasound Reports in Breast Cancer;Choi;Radiat. Oncol. J.,2023