Co-authored a study on postpartum health

Postpartum is a period when so many women struggle, and so few are being watched for risk or supported appropriately.

It’s a privilege to have contributed to a postpartum health study, Postpartum Support for Early Risk Identification Among Postpartum Women. The paper is now published in JMIR Formative Research.

The work feels motivating and impactful, and it turns out that straightforward machine learning approaches can help discover risk so that women can be better supported.

The study explores how a comprehensive postpartum SaaS platform can identify patterns of risk earlier by integrating clinical and nonclinical information. It’s a proof point for something broader: that continuous, connected data can support earlier identification of disease, rather than waiting until symptoms become severe enough to enter the healthcare system.