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      From ChatGPT to Treatment: the Future of AI and Large Language Models in Surgical Oncology

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          Large language models in medicine

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            Foundation models for generalist medical artificial intelligence

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              Is Open Access

              Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review

              Background Chatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication. Machine learning, a subset of artificial intelligence, has been proven particularly applicable in health care, with the ability for complex dialog management and conversational flexibility. Objective This review article aims to report on the recent advances and current trends in chatbot technology in medicine. A brief historical overview, along with the developmental progress and design characteristics, is first introduced. The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation. Methods A search of the literature published in the past 20 years was conducted using the IEEE Xplore, PubMed, Web of Science, Scopus, and OVID databases. The screening of chatbots was guided by the open-access Botlist directory for health care components and further divided according to the following criteria: diagnosis, treatment, monitoring, support, workflow, and health promotion. Results Even after addressing these issues and establishing the safety or efficacy of chatbots, human elements in health care will not be replaceable. Therefore, chatbots have the potential to be integrated into clinical practice by working alongside health practitioners to reduce costs, refine workflow efficiencies, and improve patient outcomes. Other applications in pandemic support, global health, and education are yet to be fully explored. Conclusions Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Indian Journal of Surgical Oncology
                Indian J Surg Oncol
                Springer Science and Business Media LLC
                0975-7651
                0976-6952
                September 2023
                October 17 2023
                September 2023
                : 14
                : 3
                : 537-539
                Article
                10.1007/s13193-023-01836-3
                37900654
                98a9849e-4a82-4bdc-9b2a-039a574a86e2
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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