Advancing women’s health through patient-centered digital data and AI
The Ensari Lab studies how digital health tools, wearable data, and AI can improve the measurement, understanding, and care of female reproductive conditions that are often overlooked. We focus on endometriosis, adenomyosis, fibroids, chronic pelvic pain, and related conditions that affect daily functioning and quality of life yet remain under-documented, difficult to measure, and too often dismissed.
Our work is driven by a practical question: are apps, wearables, and AI-based tools truly reliable, interpretable, and clinically useful for women’s health? To answer that question, we design and run real-world studies using mobile health technologies, symptom tracking, sensor data, and advanced analytics to understand how these tools perform in everyday life and how they can better support patients and clinicians.
Our research is organized around three core areas:
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Validating digital health tools: testing whether apps, wearables, and AI-based technologies are reliable, valid, and clinically meaningful for reproductive and pelvic pain conditions.
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Interpreting patient-generated data: developing ways to make symptom, behavioral, and physiological data more understandable and actionable for both patients and clinicians, with the goal of supporting better conversations, better decisions, and more agency.
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Personalizing lifestyle interventions: studying exercise and other lifestyle-based strategies to improve daily functioning, quality of life, and long-term health for people living with chronic pain conditions.
In addition to our peer-reviewed publications, we share ongoing findings and reflections through Data Bytes, our lab blog for research participants and the broader community. This work depends on the time, trust, and insight of the people who participate in our studies, and we are deeply grateful for their contributions.
The lab welcomes collaborations across research, clinical care, and public communication. To discuss collaboration opportunities, speaking invitations, or ways this work may inform policy, clinical practice, or public dialogue, please contact Dr. Ipek Ensari at ipek.ensari@mssm.edu.
We also welcome trainees, including:
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ISMMS medical students interested in a scholarly research year
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Mount Sinai OBGYN residents and fellows seeking experience in patient-generated mHealth data, women’s health, and translational AI research
To inquire about trainee opportunities, please contact Dr. Ensari at ipek.ensari@mssm.edu.