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Accepted for/Published in: JMIR Aging

Date Submitted: May 21, 2025
Date Accepted: Mar 16, 2026

The final, peer-reviewed published version of this preprint can be found here:

Leveraging Multimodal Large Language Models for Fall Risk Reduction in Older Adults in the Home: Proposed Model Design

Do J, Suresh V, Zhang L, Chavre BM, Cha J, Pugliese R

Leveraging Multimodal Large Language Models for Fall Risk Reduction in Older Adults in the Home: Proposed Model Design

JMIR Aging 2026;9:e77591

DOI: 10.2196/77591

PMID: 42127229

Leveraging Multimodal LLMs for Fall Risk Reduction in Older Adults in the Home: A Proposed Model Design

  • Justin Do; 
  • Vivaswat Suresh; 
  • Lily Zhang; 
  • Bharvi M. Chavre; 
  • Jeremy Cha; 
  • Robert Pugliese

ABSTRACT

This research letter proposes a novel model design leveraging natively multimodal large language models to identify fall risks and generate visualizations of recommended environmental modifications, aiming to improve the accessibility and impact of personalized fall prevention advice for older adults.


 Citation

Please cite as:

Do J, Suresh V, Zhang L, Chavre BM, Cha J, Pugliese R

Leveraging Multimodal Large Language Models for Fall Risk Reduction in Older Adults in the Home: Proposed Model Design

JMIR Aging 2026;9:e77591

DOI: 10.2196/77591

PMID: 42127229

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