Moving from “Surgeries” to Patients: Progress and Pitfalls While Using Machine Learning to Personalize Transfusion Prediction
Author:
Affiliation:
1. Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan.
2. Department of Learning Health Sciences, University of Michigan, Ann Arbor, Michigan.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Anesthesiology and Pain Medicine
Link
https://pubs.asahq.org/anesthesiology/article-pdf/137/1/9/671429/20220700.0-00011.pdf
Reference13 articles.
1. Practice guidelines for perioperative blood management: An updated report by the American Society of Anesthesiologists Task Force on Perioperative Blood Management;American Society of Anesthesiologists Task Force on Perioperative Blood Management;Anesthesiology,2015
2. Restrictive transfusion strategy after cardiac surgery.;Zeroual;Anesthesiology,2021
3. Restrictive versus liberal transfusion strategy in the perioperative and acute care settings: A context-specific systematic review and meta-analysis of randomized controlled trials.;Hovaguimian;Anesthesiology,2016
4. Effects of the COVID-19 pandemic on supply and use of blood for transfusion.;Stanworth;Lancet Haematol,2020
5. Personalized surgical transfusion risk prediction using machine learning to guide preoperative type and screen orders;Lou;Anesthesiology,2022
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Personalized Surgical Transfusion Risk Prediction: Comment;Anesthesiology;2022-11-08
2. Personalized Surgical Transfusion Risk Prediction: Comment;Anesthesiology;2022-11-08
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