Can we better predict who will benefit from endometriosis surgery? In this episode, Sabrina speaks with Dr. Dwayne Tucker about developing the Endometriosis Pain Index — a machine learning–based tool designed to help guide surgical decision-making and set realistic expectations for pain outcomes. From predictive modelling to patient-centred care, this conversation explores how data can transform how we approach endometriosis treatment.
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#Endometriosis #WomensHealth #SurgicalCare #HealthResearch #NextGenIn10
Resources
Endometriosis pain index: development of a model to predict poor pain-related quality of life after endometriosis surgery through machine learning analysis of registry data https://journals.lww.com/pain/fulltext/9900/endometriosis_pain_index__development_of_a_model.1125.aspx
Pelvic pain comorbidities associated with quality of life after endometriosis surgery https://pubmed.ncbi.nlm.nih.gov/37148956/
Somatic PTEN and ARID1A loss and endometriosis disease burden: a longitudinal study https://pubmed.ncbi.nlm.nih.gov/39701665/
Assessing the Utility of artificial intelligence in endometriosis: Promises and pitfalls https://pubmed.ncbi.nlm.nih.gov/38686828/
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