Longitudinal Risk Prediction for Pediatric Glioma with Temporal Deep Learning.

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Bibliographic Details
Title: Longitudinal Risk Prediction for Pediatric Glioma with Temporal Deep Learning.
Authors: Tak D; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Garomsa BA; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Zapaishchykova A; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Ye Z; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Vajapeyam S; Boston Children's Hospital, Harvard Medical School, Boston., Mahootiha M; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Pardo JCC; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Smith C; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston., Familiar AM; Children's Hospital of Philadelphia, Philadelphia., Chaunzwa TL; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston.; Memorial Sloan Kettering Cancer Center, New York., Liu KX; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston.; Boston Children's Hospital, Harvard Medical School, Boston.; Dana-Farber Cancer Institute, Boston., Prabhu SP; Boston Children's Hospital, Harvard Medical School, Boston., Bandopadhayay P; Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston.; Department of Pediatrics, Harvard Medical School, Boston.; Broad Institute of MIT and Harvard, Cambridge, Massachusetts., Nabavizadeh A; Children's Hospital of Philadelphia, Philadelphia.; Department of Neurology, Neurosurgery and Pediatrics, University of California, San Francisco, San Francisco., Mueller S; University of Pennsylvania, Philadelphia., Aerts HJWL; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston.; Radiology and Nuclear Medicine, Cardiovascular Research Institute Maastricht (CARIM) & Research Institute for Oncology and Reproduction (GROW), Maastricht University, the Netherlands., Haas-Kogan D; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston.; Boston Children's Hospital, Harvard Medical School, Boston.; Memorial Sloan Kettering Cancer Center, New York., Poussaint TY; Boston Children's Hospital, Harvard Medical School, Boston.; Memorial Sloan Kettering Cancer Center, New York., Kann BH; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston.; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston.; Memorial Sloan Kettering Cancer Center, New York.
Source: NEJM AI [NEJM AI] 2025 May; Vol. 2 (5). Date of Electronic Publication: 2025 Apr 24.
Publication Type: Journal Article
Journal Info: Publisher: NEJM Group Country of Publication: United States NLM ID: 9918752186406676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2836-9386 (Electronic) Linking ISSN: 28369386 NLM ISO Abbreviation: NEJM AI Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2836-9386
DOI:10.1056/aioa2400703