A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay.
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| Title: | A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay. |
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| Authors: | Stonko DP; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA.; R. Adams Cowley Shock Trauma Center, Baltimore, MD, USA., Weller JH; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA., Gonzalez Salazar AJ; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA., Abdou H; R. Adams Cowley Shock Trauma Center, Baltimore, MD, USA., Edwards J; R. Adams Cowley Shock Trauma Center, Baltimore, MD, USA., Hinson J; Department of Emergency Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Malone Center for Engineering in Healthcare, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Levin S; Department of Emergency Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Malone Center for Engineering in Healthcare, The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Byrne JP; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA., Sakran JV; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA., Hicks CW; Division of Vascular and Endovascular Therapy, The Johns Hopkins Hospital, Baltimore, MD, USA., Haut ER; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA.; Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of Emergency Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.; The Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, MD, USA.; Department of Health Policy and Management, Bloomberg School of Public Health, The Johns Hopkins Baltimore, MD, USA., Morrison JJ; R. Adams Cowley Shock Trauma Center, Baltimore, MD, USA., Kent AJ; Division of Trauma and Acute Care Surgery, The Johns Hopkins Hospital, The Johns Hopkins Department of Surgery, Baltimore, MD, USA. |
| Source: | Surgical innovation [Surg Innov] 2023 Jun; Vol. 30 (3), pp. 356-365. Date of Electronic Publication: 2022 Nov 17. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Publications Country of Publication: United States NLM ID: 101233809 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1553-3514 (Electronic) Linking ISSN: 15533506 NLM ISO Abbreviation: Surg Innov Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-3514 |
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| DOI: | 10.1177/15533506221139965 |
