Without Data, There Is No AI.
Every screening model is only as good as the clinical evidence it learned from. The data powering GIA® and digitalhumanOS™ was learned from more patients, more records, and more conditions than any comparable system.
The most diverse post-acute care patient dataset ever assembled. Every demographic. Every acuity level.
Longitudinal records spanning years of care — not snapshots, but complete clinical narratives.
From Alzheimer's to tardive dyskinesia. Depression to Parkinson's. Each trained on real clinical outcomes.
Small Datasets Miss Rare Conditions.
Tardive dyskinesia affects 500,000 Americans, yet most clinical datasets contain fewer than 200 confirmed cases. Our dataset captures the full spectrum of disease prevalence — including the rare conditions that small training sets consistently miss. That's the difference between a model that screens for common conditions and one that screens for all of them.
SNFs, ALFs, home health, and hospital systems — geographic and clinical diversity that prevents model bias.
De-identified, encrypted, and governed by institutional review. Patient privacy is not a feature — it is a prerequisite.
Not point-in-time snapshots. Years of clinical progression — the only way to train a model that detects disease trajectory. See our clinical research.
Without data, there is no AI. We have the data.