Optimizing patient monitoring to prevent clinical deterioration in surgical wards using machine learning.
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| Title: | Optimizing patient monitoring to prevent clinical deterioration in surgical wards using machine learning. |
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| Authors: | Jung JJ; Division of Minimally Invasive Surgery, Department of Surgery, Duke University, USA; Department of Biostatistics and Bioinformatics, Duke University, USA. Electronic address: James.Jung@duke.edu., Pou-Prom C; Data Science and Advanced Analytics, Unity Health Toronto, USA., Mamdani M; Data Science and Advanced Analytics, Unity Health Toronto, USA. |
| Source: | American journal of surgery [Am J Surg] 2025 Jul; Vol. 245, pp. 116138. Date of Electronic Publication: 2024 Dec 09. |
| Publication Type: | Editorial |
| Journal Info: | Publisher: Excerpta Medica Country of Publication: United States NLM ID: 0370473 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1883 (Electronic) Linking ISSN: 00029610 NLM ISO Abbreviation: Am J Surg Subsets: MEDLINE; In Process |
| Database: | MEDLINE Ultimate |
| ISSN: | 1879-1883 |
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| DOI: | 10.1016/j.amjsurg.2024.116138 |
