Predictive Modeling For Falls
Predictive Modeling for Falls is a computational method that distinguishes itself within the broader class of fall prevention strategies by employing statistical or machine learning techniques to identify individuals at increased risk of falling through the analysis of clinical, biomechanical, and environmental variables.
261
Publications
13.7K
Citations
1.3K
Authors
579
Institutions
Publications per year
2017–2026
128
Parents
261
Predicting the Probability for Falls in Community-Dwelling Older Adults
Anne Shumway‐Cook, Margaret Baldwin, Nayak L. Polissar et al. · Physical Therapy · 1997 · 1.6K citations · Full text
Predictors of future falls in Parkinson disease
Graham Kerr, Charles J. Worringham, Michael H. Cole et al. · Neurology · 2010 · 554 citations · Full text
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UNSW Sydney
Sydney, Australia
11 h-index
44 publications
1.8K citations

Neuroscience Research Australia
Sydney, Australia
10 h-index
32 publications
1.5K citations

The University of Sydney
Sydney, Australia
8 h-index
28 publications
1.9K citations
Skåne University Hospital
Lund, Sweden
5 h-index
14 publications
329 citations
University of Florida
Gainesville, United States
5 h-index
38 publications
2K citations
The George Institute for Global Health
Sydney, Australia
5 h-index
9 publications
559 citations

Monash University
Melbourne, Australia
4 h-index
6 publications
198 citations
Albert Einstein College of Medicine
Bronx, United States
4 h-index
8 publications
190 citations
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6 publications · 211 citations
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6 publications · 295 citations
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JAMDA · 6 publications · 311 citations
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5 publications · 185 citations
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5 publications · 394 citations
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