Wisit Cheungpasitporn, Charat Thongprayoon, Claudio Ronco, Kianoush B Kashani
{"title":"重症监护肾脏病学中的生成人工智能:应用与未来展望》。","authors":"Wisit Cheungpasitporn, Charat Thongprayoon, Claudio Ronco, Kianoush B Kashani","doi":"10.1159/000541168","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, streamlining workflows, and advancing research in this field.</p><p><strong>Summary: </strong>This review analyzes the current applications and future prospects of generative AI in critical care nephrology. Recent studies demonstrate the capabilities of LLMs in diagnostic accuracy, clinical reasoning, and continuous renal replacement therapy (CRRT) alarm troubleshooting. As we enter an era of multiagent models and automation, the integration of generative AI into critical care nephrology holds promise for improving patient care, optimizing clinical processes, and accelerating research. However, careful consideration of ethical implications and continued refinement of these technologies are essential for their responsible implementation in clinical practice. This review explores the current and potential applications of generative AI in nephrology, focusing on clinical decision support, patient education, research, and medical education. Additionally, we examine the challenges and limitations of AI implementation, such as privacy concerns, potential bias, and the necessity for human oversight.</p><p><strong>Key messages: </strong>(i) LLMs have shown potential in enhancing diagnostic accuracy, clinical reasoning, and CRRT alarm troubleshooting in critical care nephrology. (ii) Generative AI offers promising applications in patient education, literature review, and academic writing within the field of nephrology. (iii) The integration of AI into electronic health records and clinical workflows presents both opportunities and challenges for improving patient care and research. (iv) Addressing ethical concerns, ensuring data privacy, and maintaining human oversight are crucial for the responsible implementation of AI in critical care nephrology.</p>","PeriodicalId":8953,"journal":{"name":"Blood Purification","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generative AI in Critical Care Nephrology: Applications and Future Prospects.\",\"authors\":\"Wisit Cheungpasitporn, Charat Thongprayoon, Claudio Ronco, Kianoush B Kashani\",\"doi\":\"10.1159/000541168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, streamlining workflows, and advancing research in this field.</p><p><strong>Summary: </strong>This review analyzes the current applications and future prospects of generative AI in critical care nephrology. Recent studies demonstrate the capabilities of LLMs in diagnostic accuracy, clinical reasoning, and continuous renal replacement therapy (CRRT) alarm troubleshooting. As we enter an era of multiagent models and automation, the integration of generative AI into critical care nephrology holds promise for improving patient care, optimizing clinical processes, and accelerating research. However, careful consideration of ethical implications and continued refinement of these technologies are essential for their responsible implementation in clinical practice. This review explores the current and potential applications of generative AI in nephrology, focusing on clinical decision support, patient education, research, and medical education. Additionally, we examine the challenges and limitations of AI implementation, such as privacy concerns, potential bias, and the necessity for human oversight.</p><p><strong>Key messages: </strong>(i) LLMs have shown potential in enhancing diagnostic accuracy, clinical reasoning, and CRRT alarm troubleshooting in critical care nephrology. (ii) Generative AI offers promising applications in patient education, literature review, and academic writing within the field of nephrology. (iii) The integration of AI into electronic health records and clinical workflows presents both opportunities and challenges for improving patient care and research. (iv) Addressing ethical concerns, ensuring data privacy, and maintaining human oversight are crucial for the responsible implementation of AI in critical care nephrology.</p>\",\"PeriodicalId\":8953,\"journal\":{\"name\":\"Blood Purification\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Blood Purification\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1159/000541168\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blood Purification","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000541168","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEMATOLOGY","Score":null,"Total":0}
Generative AI in Critical Care Nephrology: Applications and Future Prospects.
Background: Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, streamlining workflows, and advancing research in this field.
Summary: This review analyzes the current applications and future prospects of generative AI in critical care nephrology. Recent studies demonstrate the capabilities of LLMs in diagnostic accuracy, clinical reasoning, and continuous renal replacement therapy (CRRT) alarm troubleshooting. As we enter an era of multiagent models and automation, the integration of generative AI into critical care nephrology holds promise for improving patient care, optimizing clinical processes, and accelerating research. However, careful consideration of ethical implications and continued refinement of these technologies are essential for their responsible implementation in clinical practice. This review explores the current and potential applications of generative AI in nephrology, focusing on clinical decision support, patient education, research, and medical education. Additionally, we examine the challenges and limitations of AI implementation, such as privacy concerns, potential bias, and the necessity for human oversight.
Key messages: (i) LLMs have shown potential in enhancing diagnostic accuracy, clinical reasoning, and CRRT alarm troubleshooting in critical care nephrology. (ii) Generative AI offers promising applications in patient education, literature review, and academic writing within the field of nephrology. (iii) The integration of AI into electronic health records and clinical workflows presents both opportunities and challenges for improving patient care and research. (iv) Addressing ethical concerns, ensuring data privacy, and maintaining human oversight are crucial for the responsible implementation of AI in critical care nephrology.
期刊介绍:
Practical information on hemodialysis, hemofiltration, peritoneal dialysis and apheresis is featured in this journal. Recognizing the critical importance of equipment and procedures, particular emphasis has been placed on reports, drawn from a wide range of fields, describing technical advances and improvements in methodology. Papers reflect the search for cost-effective solutions which increase not only patient survival but also patient comfort and disease improvement through prevention or correction of undesirable effects. Advances in vascular access and blood anticoagulation, problems associated with exposure of blood to foreign surfaces and acute-care nephrology, including continuous therapies, also receive attention. Nephrologists, internists, intensivists and hospital staff involved in dialysis, apheresis and immunoadsorption for acute and chronic solid organ failure will find this journal useful and informative. ''Blood Purification'' also serves as a platform for multidisciplinary experiences involving nephrologists, cardiologists and critical care physicians in order to expand the level of interaction between different disciplines and specialities.