Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial
Camran R Nezhat1, Tomiko T Oskotsky2, Joshua F Robinson3
1Center for Special Minimally Invasive and Robotic Surgery, Camran Nezhat Institute, Stanford University Medical Center, University of California, San Francisco, Woodside, CA 94061 USA.
Abstract:
Endometriosis is an enigmatic disease whose diagnosis and management are being transformed through innovative surgical, molecular, and computational technologies. Integrating single-cell and other omic disease data with clinical and surgical metadata can identify multiple disease subtypes with translation to novel diagnostics and therapeutics. Herein, we present real-world perspectives on endometriosis and the importance of multidisciplinary collaboration in informing molecular, epidemiologic, and cell-specific data in the clinical and surgical contexts.
