Our lab conducts studies on mobile health (mHealth) technologies and machine learning methods for complex patient-generated data toward improving chronic disease characterization and patient self-management. Our research is grounded in women’s reproductive health conditions (e.g., endometriosis, chronic pelvic pain disorders; CPPDs) and populations at increased risk for health disparities (e.g., sexual and gender minorities; SGM). To this end, we investigate: 1) Integration of mobile self-tracking and wearable data to augment electronic health records (EHRs) for improving clinical decision making and patient self-management, 2) Use of direct patient input for elucidating conditions that are poorly understood and not well documented in electronic health records, and 3) development of patient-centered mHealth measures and intervention tools that combine multifarious data streams.