Camran R Nezhat, Tomiko T Oskotsky, Joshua F Robinson, Susan J Fisher, Angie Tsuei, Binya Liu, Juan C Irwin, Brice Gaudilliere, Marina Sirota, David K Stevenson, Linda C Giudice
{"title":"Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence.","authors":"Camran R Nezhat, Tomiko T Oskotsky, Joshua F Robinson, Susan J Fisher, Angie Tsuei, Binya Liu, Juan C Irwin, Brice Gaudilliere, Marina Sirota, David K Stevenson, Linda C Giudice","doi":"10.1038/s44294-024-00052-w","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":520241,"journal":{"name":"npj women's health","volume":"3 1","pages":"8"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11802455/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj women's health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44294-024-00052-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/6 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.