Predicting Patient-Reported Outcomes Following Surgery Using Machine Learning.
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| Title: | Predicting Patient-Reported Outcomes Following Surgery Using Machine Learning. |
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| Authors: | Hassan AM; Department of Plastic and Reconstructive Surgery, 571198The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Biaggi-Ondina A; Department of Plastic and Reconstructive Surgery, 571198The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Rajesh A; Department of Surgery, 14742University of Texas Health Science Center, San Antonio, TX, USA., Asaad M; Department of Plastic Surgery, 6595University of Pittsburgh Medical Center, Pittsburgh, PA, USA., Nelson JA; Department of Plastic & Reconstructive Surgery, 5803Memorial Sloan Kettering Cancer Center, New York, NY, USA., Coert JH; Department of Plastic and Reconstructive Surgery, 8124University Medical Center Utrecht, Utrecht, Netherlands., Mehrara BJ; Department of Plastic & Reconstructive Surgery, 5803Memorial Sloan Kettering Cancer Center, New York, NY, USA., Butler CE; Department of Plastic and Reconstructive Surgery, 571198The University of Texas MD Anderson Cancer Center, Houston, TX, USA. |
| Source: | The American surgeon [Am Surg] 2023 Jan; Vol. 89 (1), pp. 31-35. Date of Electronic Publication: 2022 Jun 18. |
| Publication Type: | Review; Journal Article |
| Journal Info: | Publisher: SAGE Publications in association with Southeastern Surgical Congress Country of Publication: United States NLM ID: 0370522 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1555-9823 (Electronic) Linking ISSN: 00031348 NLM ISO Abbreviation: Am Surg Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1555-9823 |
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| DOI: | 10.1177/00031348221109478 |
