{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9"],"submitter":["Yang X"],"pubmed_abstract":["<h4>Background</h4>Falls are one of the leading causes of injury or death among older adults. Falls occurring in individuals during hospitalization, as an adverse event, are a key concern for health care institutions. Identifying older adults at high risk of falls in clinical settings enables early interventions, thereby reducing the incidence of falls.<h4>Objective</h4>This study aims to develop and validate machine learning models to predict the risk of falls among hospitalized older adults.<h4>Methods</h4>This study retrospectively analyzed data from a tertiary general hospital in China, including 342 older adults who experienced falls and 684 randomly matched nonfallers, between January 2018 and December 2024, encompassing demographic information, comorbidities, laboratory parameters, "],"journal":["JMIR aging"],"pagination":["e80602"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12767673"],"repository":["biostudies-literature"],"pubmed_title":["Development and Validation of Machine Learning Models for Predicting Falls Among Hospitalized Older Adults: Retrospective Cross-Sectional Study."],"pmcid":["PMC12767673"],"pubmed_authors":["Su D","Li J","Zhang M","Wei Z","Zhang S","Xu J","Dai X","Yang X","Li X","Bao M","Li Y","Mo N","Ren J","Zhang Y","Chen X","Wang Z"],"additional_accession":[]},"is_claimable":false,"name":"Development and Validation of Machine Learning Models for Predicting Falls Among Hospitalized Older Adults: Retrospective Cross-Sectional Study.","description":"<h4>Background</h4>Falls are one of the leading causes of injury or death among older adults. Falls occurring in individuals during hospitalization, as an adverse event, are a key concern for health care institutions. Identifying older adults at high risk of falls in clinical settings enables early interventions, thereby reducing the incidence of falls.<h4>Objective</h4>This study aims to develop and validate machine learning models to predict the risk of falls among hospitalized older adults.<h4>Methods</h4>This study retrospectively analyzed data from a tertiary general hospital in China, including 342 older adults who experienced falls and 684 randomly matched nonfallers, between January 2018 and December 2024, encompassing demographic information, comorbidities, laboratory parameters, ","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Jan","modification":"2026-06-06T11:55:24.041Z","creation":"2026-05-30T03:09:07.694Z"},"accession":"S-EPMC12767673","cross_references":{"pubmed":["41489988"],"doi":["10.2196/80602"]}}