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AI might finally shrink the brutal seven-to-eleven-year journey to endometriosis diagnosis—but only if we pair smarter tools with real clinical judgment. We sit down with Professor Gaby Moawad, a global leader in robotic surgery and endometriosis management, to unpack where technology genuinely helps and where hype can harm. From machine learning that flags lesions on imaging to microRNA biomarkers that stratify risk, we chart what’s promising, what’s premature, and how to avoid black-box mistakes.

We take you inside the OR to explore 3D modeling that transforms standard MRIs into color-coded maps of the pelvis in minutes, then overlays them in surgery for more complete, nerve-sparing excision. Precision is powerful, but ethics matter: surgeons must remain the final guardrail when algorithms error. Beyond the tech, we face the tough questions—why one-third of patients still have pain after surgery, how musculoskeletal drivers and pelvic floor dysfunction are missed, and why 30–50% of endometriosis surgeries may be unnecessary without comprehensive evaluation and aftercare.

We also probe hot topics: the seductive idea of “reprogramming” lesions through immune or epigenetic pathways, the complex links between COVID, vaccination, and inflammatory flares, and the huge research gaps that keep care one-size-fits-all. Subtyping, patient-reported outcomes like fatigue and bloating, and microbiome-informed strategies could reshape treatment, but only with rigorous studies and honest communication. The path forward is center-based, team-driven care anchored by informed consent that puts full information—and real choices—in your hands.

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