Machine Learning for Sepsis Prediction: Prospects and Challenges

Journal Article Machine Learning for Sepsis Prediction: Prospects and Challenges Get access He S Yang He S Yang Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, 10065, United States Address correspondence to this author at: Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, 525 E. 68th Str., New York, NY, 10065, United States. E-mail hey9012@med.cornell.edu. Search for other works by this author on: Oxford Academic Google Scholar Clinical Chemistry, Volume 70, Issue 3, March 2024, Pages 465–467, https://doi.org/10.1093/clinchem/hvae006 Published: 02 March 2024 Article history Received: 18 December 2023 Accepted: 11 January 2024 Published: 02 March 2024