From Noise to Signal: Unveiling Treatment Effects from Digital Health Data through Pharmacology-Informed Neural-SDE

Understand

Digital health technologies (DHT), such as wearable devices, provide personalized, continuous, and real-time monitoring of patient.

• These technologies are contributing to the development of novel therapies and personalized medicine.
• Gaining insight from these technologies requires appropriate modeling techniques to capture clinically-relevant changes in disease state.
• The data generated from these devices is characterized by being stochastic in nature, may have missing elements, and exhibits considerable inter-individual variability - thereby making it difficult to analyze using traditional longitudinal modeling techniques.