{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/does-the-artificial-intelligence-clinician","title":"Does the \"Artificial Intelligence Clinician\" learn optimal treatment strategies for sepsis in intensive care?","arxiv_id":"1902.03271","date":"2019-02-08","proceeding":null,"authors":["Russell Jeter","Christopher Josef","Supreeth Shashikumar","Shamim Nemati"],"abstract":"From 2017 to 2018 the number of scientific publications found via PubMed\nsearch using the keyword \"Machine Learning\" increased by 46% (4,317 to 6,307).\nThe results of studies involving machine learning, artificial intelligence\n(AI), and big data have captured the attention of healthcare practitioners,\nhealthcare managers, and the public at a time when Western medicine grapples\nwith unmitigated cost increases and public demands for accountability. The\ncomplexity involved in healthcare applications of machine learning and the size\nof the associated data sets has afforded many researchers an uncontested\nopportunity to satisfy these demands with relatively little oversight. In a\nrecent Nature Medicine article, \"The Artificial Intelligence Clinician learns\noptimal treatment strategies for sepsis in intensive care,\" Komorowski and his\ncoauthors propose methods to train an artificial intelligence clinician to\ntreat sepsis patients with vasopressors and IV fluids. In this post, we will\nclosely examine the claims laid out in this paper. In particular, we will study\nthe individual treatment profiles suggested by their AI Clinician to gain\ninsight into how their AI Clinician intends to treat patients on an individual\nlevel.","url_abs":"http://arxiv.org/abs/1902.03271v1","url_pdf":"http://arxiv.org/pdf/1902.03271v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"does-the-artificial-intelligence-clinician","repo_url":"https://github.com/point85AI/Policy-Iteration-AI-Clinician","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1902.03271","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}