A personalized prediction of longitudinal growth using People-Like-Me methods.

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Bibliographic Details
Title: A personalized prediction of longitudinal growth using People-Like-Me methods.
Authors: Jin X; Department of Biostatistics and Informatics, Colorado School of Public Health, CO, United States., Juarez-Colunga E; Department of Biostatistics and Informatics, Colorado School of Public Health, CO, United States; VA Eastern Colorado Geriatric Research, Education, and Clinical Center (GRECC), VA Eastern Colorado Health Care System, CO, United States. Electronic address: elizabeth.juarez-colunga@cuanschutz.edu., Buuren SV; Department of Methodology and Statistics, Utrecht University, The Netherlands., Colborn K; School of Medicine, University of Colorado, CO, United States., Rosenfeld M; Department of Pediatrics, Seattle Children's Hospital in University of Washington, WA, United States., Graber J; Denver/Seattle Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, CO, United States; Department of Physical Medicine and Rehabilitation, University of Colorado, CO, United States., Stevens-Lapsley J; Department of Physical Medicine and Rehabilitation, University of Colorado, CO, United States; VA Eastern Colorado Geriatric Research, Education, and Clinical Center (GRECC), VA Eastern Colorado Health Care System, CO, United States.
Source: Computers in biology and medicine [Comput Biol Med] 2025 Dec; Vol. 199, pp. 111281. Date of Electronic Publication: 2025 Nov 13.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-0534
DOI:10.1016/j.compbiomed.2025.111281