Improving ICU Risk Predictive Models Through Automation Designed for Resiliency Against Documentation Bias.
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| Title: | Improving ICU Risk Predictive Models Through Automation Designed for Resiliency Against Documentation Bias. |
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| Authors: | Liu X; Johnson & Johnson, Data Science Portfolio Management, New Brunswick, NJ., Armaignac DL; Baptist Health South Florida, Miami, FL., Becker C; Westchester Medical Center, Valhalla, NY., Hiddleson C; Emory Healthcare, Atlanta, GA., Dubouchet EM; Baptist Health South Florida, Miami, FL., Rincon T; Blue Cirrus Consulting, Greenville, SC., Amelung PJ; Philips, Connected Care, Virtual Care Solutions, Baltimore, MD., French R; Philips, Connected Care, Virtual Care Solutions, Baltimore, MD., Scurlock C; Westchester Medical Center, Valhalla, NY.; New affiliation for Dr. Scurlock: Equum Medical, New York, NY., Atallah L; Philips, Connected Care, Virtual Care Solutions, Baltimore, MD., Badawi O; University of Maryland School of Pharmacy, Baltimore, MD. |
| Source: | Critical care medicine [Crit Care Med] 2023 Mar 01; Vol. 51 (3), pp. 376-387. Date of Electronic Publication: 2022 Dec 27. |
| Publication Type: | Randomized Controlled Trial; Multicenter Study; Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0355501 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1530-0293 (Electronic) Linking ISSN: 00903493 NLM ISO Abbreviation: Crit Care Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1530-0293 |
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| DOI: | 10.1097/CCM.0000000000005750 |
