Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence
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 w...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | npj Women's Health |
| Online Access: | https://doi.org/10.1038/s44294-024-00052-w |
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| _version_ | 1823861506791440384 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Camran R. Nezhat |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d3ca47c994b94a5597af06cc6d169d6f |
| institution | Kabale University |
| issn | 2948-1716 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Women's Health |
| spelling | doaj-art-d3ca47c994b94a5597af06cc6d169d6f2025-02-09T13:00:35ZengNature Portfolionpj Women's Health2948-17162025-02-013111610.1038/s44294-024-00052-wReal world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligenceCamran R. Nezhat0Tomiko T. Oskotsky1Joshua F. Robinson2Susan J. Fisher3Angie Tsuei4Binya Liu5Juan C. Irwin6Brice Gaudilliere7Marina Sirota8David K. Stevenson9Linda C. Giudice10Center for Special Minimally Invasive and Robotic Surgery, Camran Nezhat Institute, Stanford University Medical Center, University of California, San FranciscoBakar Computational Health Sciences Institute, University of California San FranciscoCenter for Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San FranciscoCenter for Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San FranciscoCenter for Special Minimally Invasive and Robotic Surgery, Camran Nezhat InstituteDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of California San FranciscoDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of California San FranciscoDepartment of Anesthesiology, Pain, and Perioperative Medicine, and (courtesy) Pediatrics, Stanford UniversityBakar Computational Health Sciences Institute, University of California San FranciscoDepartment of Pediatrics, Stanford UniversityDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of California San FranciscoAbstract 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.https://doi.org/10.1038/s44294-024-00052-w |
| spellingShingle | 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 Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence npj Women's Health |
| title | Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence |
| title_full | Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence |
| title_fullStr | Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence |
| title_full_unstemmed | Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence |
| title_short | Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence |
| title_sort | real world perspectives on endometriosis disease phenotyping through surgery omics health data and artificial intelligence |
| url | https://doi.org/10.1038/s44294-024-00052-w |
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