Wisit Cheungpasitporn, Charat Thongprayoon, Kianoush B Kashani
{"title":"Advances in critical care nephrology through artificial intelligence.","authors":"Wisit Cheungpasitporn, Charat Thongprayoon, Kianoush B Kashani","doi":"10.1097/MCC.0000000000001202","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>This review explores the transformative advancement, potential application, and impact of artificial intelligence (AI), particularly machine learning (ML) and large language models (LLMs), on critical care nephrology.</p><p><strong>Recent findings: </strong>AI algorithms have demonstrated the ability to enhance early detection, improve risk prediction, personalize treatment strategies, and support clinical decision-making processes in acute kidney injury (AKI) management. ML models can predict AKI up to 24-48 h before changes in serum creatinine levels, and AI has the potential to identify AKI sub-phenotypes with distinct clinical characteristics and outcomes for targeted interventions. LLMs and generative AI offer opportunities for automated clinical note generation and provide valuable patient education materials, empowering patients to understand their condition and treatment options better. To fully capitalize on its potential in critical care nephrology, it is essential to confront the limitations and challenges of AI implementation, including issues of data quality, ethical considerations, and the necessity for rigorous validation.</p><p><strong>Summary: </strong>The integration of AI in critical care nephrology has the potential to revolutionize the management of AKI and continuous renal replacement therapy. While AI holds immense promise for improving patient outcomes, its successful implementation requires ongoing training, education, and collaboration among nephrologists, intensivists, and AI experts.</p>","PeriodicalId":10851,"journal":{"name":"Current Opinion in Critical Care","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Critical Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/MCC.0000000000001202","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/30 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose of review: This review explores the transformative advancement, potential application, and impact of artificial intelligence (AI), particularly machine learning (ML) and large language models (LLMs), on critical care nephrology.
Recent findings: AI algorithms have demonstrated the ability to enhance early detection, improve risk prediction, personalize treatment strategies, and support clinical decision-making processes in acute kidney injury (AKI) management. ML models can predict AKI up to 24-48 h before changes in serum creatinine levels, and AI has the potential to identify AKI sub-phenotypes with distinct clinical characteristics and outcomes for targeted interventions. LLMs and generative AI offer opportunities for automated clinical note generation and provide valuable patient education materials, empowering patients to understand their condition and treatment options better. To fully capitalize on its potential in critical care nephrology, it is essential to confront the limitations and challenges of AI implementation, including issues of data quality, ethical considerations, and the necessity for rigorous validation.
Summary: The integration of AI in critical care nephrology has the potential to revolutionize the management of AKI and continuous renal replacement therapy. While AI holds immense promise for improving patient outcomes, its successful implementation requires ongoing training, education, and collaboration among nephrologists, intensivists, and AI experts.
期刊介绍:
Current Opinion in Critical Care delivers a broad-based perspective on the most recent and most exciting developments in critical care from across the world. Published bimonthly and featuring thirteen key topics – including the respiratory system, neuroscience, trauma and infectious diseases – the journal’s renowned team of guest editors ensure a balanced, expert assessment of the recently published literature in each respective field with insightful editorials and on-the-mark invited reviews.