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《大语言模型:医疗行业的变革者》(英文)

Large language models: game-changers in the healthcare industry

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【作者】 董彬张立袁家佳陈杨李全政沈琳

【Author】 Bin Dong;Li Zhang;Jiajia Yuan;Yang Chen;Quanzheng Li;Lin Shen;Beijing International Center for Mathematical Research, Peking University;Center for Machine Learning Research, Peking University;Peking University Changsha Institute for Computing and Digital Economy;Center for Data Science, Peking University;Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute;Massachusetts General Hospital;Harvard Medical School;

【通讯作者】 李全政;沈琳;

【机构】 Beijing International Center for Mathematical Research, Peking UniversityCenter for Machine Learning Research, Peking UniversityPeking University Changsha Institute for Computing and Digital EconomyCenter for Data Science, Peking UniversityDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and InstituteMassachusetts General HospitalHarvard Medical School

【摘要】 The healthcare industry faces core challenges, including increasingly complex operational processes and entities, the rapid development of medical knowledge, and the rising demand for interdisciplinary expertise. The complexity of medical processes is evident in every aspect, from patient appointments, diagnoses,and treatments to follow-up tasks, all of which involve intricate data processing and decision-making procedures. At the same time, the challenges concerning the regional disparities in healthcare services and the difficulty of spreading advanced medical technologies are becoming prominent. These factors include not only patient medical records but also the rational allocation and efficient management of medical resources. Moreover, the individual differences among different patients, such as their distinct medical histories, genetic backgrounds, living environments, and psychological states, and the difficulty of training qualified doctors in a short period pose additional challenges to maintaining efficiency and sustainability while providing high-quality and personalized treatment plans.

【Abstract】 The healthcare industry faces core challenges, including increasingly complex operational processes and entities, the rapid development of medical knowledge, and the rising demand for interdisciplinary expertise. The complexity of medical processes is evident in every aspect, from patient appointments, diagnoses,and treatments to follow-up tasks, all of which involve intricate data processing and decision-making procedures. At the same time, the challenges concerning the regional disparities in healthcare services and the difficulty of spreading advanced medical technologies are becoming prominent. These factors include not only patient medical records but also the rational allocation and efficient management of medical resources. Moreover, the individual differences among different patients, such as their distinct medical histories, genetic backgrounds, living environments, and psychological states, and the difficulty of training qualified doctors in a short period pose additional challenges to maintaining efficiency and sustainability while providing high-quality and personalized treatment plans.

【基金】 supported by the National Natural Science Foundation of China (U22A20327, 12090022, 11831002, 81801778, and 82203881);Beijing Natural Science Foundation (7222021);Beijing Hospitals Authority Youth Programme (QML20231115);Clinical Medicine Plus X-Young Scholars Project of Peking University (PKU2023LCXQ041)
  • 【文献出处】 Science Bulletin ,科学通报(英文版) , 编辑部邮箱 ,2025年03期
  • 【分类号】TP18
  • 【下载频次】13
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