Machine-learning fall prediction algorithm
Machine-learning fall prediction algorithm has been studied in 1 paper since 2026: 1 observational study in people; 1 in the past year. The newest paper, Feb 2, 2026: “Impact of artificial intelligence on physiotherapist fall predictions in long-term care residents: Observational study (Preprint)”.
1 paper studies it2 findingsUpdated
See all 1 papers on machine-learning fall prediction algorithm
At a glance
The findings reach people, from one lab or study. 1 lab.
“There was an increase in physiotherapists’ ability to discriminate between a resident falling and not falling within the next four weeks after reviewing the results of the algorithm”
None of its findings points the other way.
- 1 lab
- Humans1
What did studies of machine-learning fall prediction algorithm find?
2Studies of machine-learning fall prediction algorithm measured 2 outcomes; the most studied are Physiotherapist decisional confidence (1 study) and Fall prediction accuracy (1).
Physiotherapist decisional confidence
no changein humans1
1 study
Physiotherapist decisional confidence
no changein humans1
Machine-learning fall prediction algorithm was not clearly linked with physiotherapist decisional confidence in humans.
“ML-based prediction models may improve a physiotherapist’s fall risk assessment but they do not improve their decisional confidence”
Humansn = 44
Preprint
Fall prediction accuracy
upin humans1
1 study
Fall prediction accuracy
upin humans1
Machine-learning fall prediction algorithm is linked with better fall prediction accuracy in humans (pre-algorithm AUC 0.78, post-algorithm AUC 0.86).
“There was an increase in physiotherapists’ ability to discriminate between a resident falling and not falling within the next four weeks after reviewing the results of the algorithm”
Humansn = 44
Preprint