The Evolving Role of Machine Learning in the Analysis of Outcomes After Pediatric and Congenital Cardiac Surgery.
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| Title: | The Evolving Role of Machine Learning in the Analysis of Outcomes After Pediatric and Congenital Cardiac Surgery. |
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| Authors: | Jacobs JP; Congenital Heart Center Division of Cardiothoracic Surgery Departments of Surgery and Pediatrics University of Florida, 1600 SW Archer Rd, Gainesville, FL 32608. Electronic address: jeffreyjacobs@ufl.edu., Kumar SR; Division of Cardiothoracic Surgery Children's Nebraska University of Nebraska Medical Center Omaha, Nebraska., Overman DM; Division of Cardiovascular Surgery, Mayo Clinic-Children's Minnesota Cardiovascular Collaborative, Minneapolis, Minnesota., Dearani JA; Division of Cardiovascular Surgery, Mayo Clinic-Children's Minnesota Cardiovascular Collaborative, Minneapolis, Minnesota., Romano JC; Department of Cardiac Surgery, University of Michigan, Ann Arbor, Michigan. |
| Source: | The Annals of thoracic surgery [Ann Thorac Surg] 2024 Jul; Vol. 118 (1), pp. 207-208. Date of Electronic Publication: 2023 Dec 09. |
| Publication Type: | Editorial; Comment |
| Journal Info: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 15030100R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1552-6259 (Electronic) Linking ISSN: 00034975 NLM ISO Abbreviation: Ann Thorac Surg Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1552-6259 |
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| DOI: | 10.1016/j.athoracsur.2023.11.030 |
