aceAnonymized but Useful Synthetic Tabular Health Data for AI based Fall Risk Assessment
Artificial Intelligence (AI) bears potential for improving health care, but this depends on the availability of open-access, realistic, and useful data. To facilitate AI model development in health care we release SynTabFall, a novel synthetic dataset for fall risk assessment. With a total of 745,380 samples and 44 attributes such as demographics, diseases, mobility and cognition related risk factors, this tabular dataset allows for training fall risk prediction models without access to the original patient data…
Release of SynTabFall synthetic dataset with 745,380 samples allows training fall-risk prediction models without original patient data while achieving performance on par with models trained on real data.
Evidence
- Peer-reviewedScientific Data2026-07-24
How should this claim be treated?
Truvace Impact Record TRV-2026-0583, v1: “Anonymized but Useful Synthetic Tabular Health Data for AI based Fall Risk Assessment.” Truvace, 2026-07-29. /record/TRV-2026-0583 (accessed at citation time). sha256 c460f7522c812894…
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