ML-Based Fall Risk Prediction to Substitute Personal Assistance for Hospitalized Elderly: Integrating Geriatric Assessment and E-Health Records
- Title
- ML-Based Fall Risk Prediction to Substitute Personal Assistance for Hospitalized Elderly: Integrating Geriatric Assessment and E-Health Records
- Creator
- Rajan, Jinu Sara; Vinay, M.
- Description
- Geriatric assessment serves as a holistic evaluation tool, encompassing various aspects of the elderly individual's health, including physical function, cognition, and psychosocial factors. Integration of CGA data with EHRs allows for a comprehensive analysis of the individual's health status and medical history, providing valuable insights into their risk factors for falls. The ML-based predictive model developed in this study utilizes these integrated data sources to identify patterns and trends associated with fall occurrences among hospitalized elderly patients. By analysing various variables, including mobility indicators, medication usage, and previous fall history, the model can generate accurate predictions of fall risks for individual patients. This ML-driven approach has the potential to significantly improve patient safety and quality of care by enabling healthcare providers to pre-emptively identify and address fall risks among hospitalized elderly individuals, thereby reducing the reliance on constant personal assistance while ensuring optimal patient outcomes. 2025 by IGI Global Scientific Publishing.
- Source
- Assistive Technology Solutions for Aging Adults and Individuals with Disabilities;pp.281-308
- Date
- 01-01-2025
- Publisher
- IGI Global
- Coverage
- Rajan J.S., Christ University, India; Vinay M., Christ University, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-836936309-6; 979-836936308-9;
- Format
- online
- Language
- English
- Type
- Book chapter
Collection
Citation
Rajan, Jinu Sara; Vinay, M., “ML-Based Fall Risk Prediction to Substitute Personal Assistance for Hospitalized Elderly: Integrating Geriatric Assessment and E-Health Records,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/24972.