Article

Benchmarking Machine Learning Architectures forMenstrual Recovery Prediction Using PhysiologicallyInformed Synthetic Wearable Data

2026-04-27

Abstract excerpt

<title>Abstract</title> <p>Secondary amenorrhea is a heterogeneous condition with implications for reproductive, cardiovascular, and bone health. Existing machine learning approaches in menstrual health focus on cycle prediction rather than recovery modeling in pathological conditions. We present a proof-of-concept framework to model menstrual recovery within three months from non-invasive wearable-derived physio...

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Literature Corpus work: 6d0df38c-65d7-5153-9818-8e9f705a8d74
DOI: 10.21203/rs.3.rs-9430731/v1

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