Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.
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| Title: | Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study. |
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| Authors: | Nield LE; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. lynne.nield@sunnybrook.ca., Manlhiot C; Department of Pediatrics, Blalock-Taussig-Thomas Congenital Heart Center, Johns Hopkins University, Baltimore, MD, USA., Magor K; University of Toronto, Toronto, Canada., Freud L; The Hospital for Sick Children, Toronto, Canada., Chinni B; Department of Pediatrics, Blalock-Taussig-Thomas Congenital Heart Center, Johns Hopkins University, Baltimore, MD, USA., Ims A; Department of Pediatrics, Blalock-Taussig-Thomas Congenital Heart Center, Johns Hopkins University, Baltimore, MD, USA., Melamed N; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada., Nevo O; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada., Van Mieghem T; Department of Obstetrics and Gynaecology, Mount Sinai Hospital Toronto, University of Toronto, Toronto, Canada., Weisz D; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada., Ronzoni S; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. |
| Source: | Pediatric cardiology [Pediatr Cardiol] 2025 Apr; Vol. 46 (4), pp. 895-901. Date of Electronic Publication: 2024 May 09. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Verlag Country of Publication: United States NLM ID: 8003849 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1971 (Electronic) Linking ISSN: 01720643 NLM ISO Abbreviation: Pediatr Cardiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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