Digital Health
3 Results were found on Technologies
Sub Category Name
Source Invariant Machine Learning Platform for Robust Clinical Condition Prediction
Clinical and digital‑health models must integrate data from many heterogeneous and rapidly changing sources (EHR systems, devices, apps), making conventional models fragile when inputs or formats change. Maintaining and re‑validating separate models for each data source or version is costly and slow, limiting deployment of AI‑based decision support at scale. The technology Autoencoder modules trained […] Read More >
Smartwatch-Informed Participant Matching and Outcome Optimization in Clinical Trials
Randomized controlled trials (RCTs) carry prohibitive costs of up to hundreds of thousands of dollars per participant. Traditional matching approaches relying solely on general health status, disease progression, and demographic factors fail to optimize statistical accuracy, resulting in larger-than-necessary trials at high costs. Technology • A Smartwatch-Informed Matching (SIM) protocol for enhanced clinical trial design […] Read More >
Micropatterning Cells and Spheroids in 3D Hydrogels
Control over cell organization within 3D hydrogels, strategically placing cells in specific locations, holds significant potential for engineering tissues with precise and intricate architectures, as well as for advancing drug testing applications. Although methods for micropatterning cells on 2D substrates are well-established and widely accessible, achieving cell micropatterning within biomimetic 3D hydrogels—mimicking the soft cellular […] Read More >
