A systematic review of large language models (LLMs) in clinical and surgical settings was conducted, identifying 34 relevant articles published in 2023. These studies explored various applications of LLMs, including diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks in clinical settings. In surgical contexts, LLMs assist with documentation, surgical planning, and intraoperative guidance. However, concerns about accuracy, bias, and patient privacy remain. The review highlights the potential of LLMs to enhance healthcare delivery but emphasizes the need for further research to address their limitations. LLMs should be viewed as tools to complement, not replace, healthcare professionals. The review also discusses non-clinical applications, such as medical education, patient support, and research, while noting the challenges of bias, data quality, and ethical considerations. Future research should focus on improving LLM accuracy, expanding their clinical and surgical applications, integrating them with healthcare systems, and addressing ethical concerns. Overall, LLMs show promise in enhancing healthcare but require careful implementation to ensure safety and effectiveness.A systematic review of large language models (LLMs) in clinical and surgical settings was conducted, identifying 34 relevant articles published in 2023. These studies explored various applications of LLMs, including diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks in clinical settings. In surgical contexts, LLMs assist with documentation, surgical planning, and intraoperative guidance. However, concerns about accuracy, bias, and patient privacy remain. The review highlights the potential of LLMs to enhance healthcare delivery but emphasizes the need for further research to address their limitations. LLMs should be viewed as tools to complement, not replace, healthcare professionals. The review also discusses non-clinical applications, such as medical education, patient support, and research, while noting the challenges of bias, data quality, and ethical considerations. Future research should focus on improving LLM accuracy, expanding their clinical and surgical applications, integrating them with healthcare systems, and addressing ethical concerns. Overall, LLMs show promise in enhancing healthcare but require careful implementation to ensure safety and effectiveness.