Toward precision prognosis: Predicting recurrence-free survival in high-grade serous ovarian cancer patients using multi-time point clinical and computed tomography radiomics data.
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| Title: | Toward precision prognosis: Predicting recurrence-free survival in high-grade serous ovarian cancer patients using multi-time point clinical and computed tomography radiomics data. |
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| Authors: | Roller L; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America., Zhou N; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America., Atre I; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America., Xiong N; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America., Li J; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America., Cheng SC; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America., Liu N; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America., Lacad D; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America., Adjei M; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America., Matulonis UA; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America., Konstantinopoulos PA; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America., Liu JF; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America., Tayob N; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America., Stover EH; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America. Electronic address: elizabeth_stover@dfci.harvard.edu., Shinagare AB; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America. |
| Source: | Gynecologic oncology [Gynecol Oncol] 2026 Jul 02; Vol. 211, pp. 98-107. Date of Electronic Publication: 2026 Jul 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Academic Press Country of Publication: United States NLM ID: 0365304 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-6859 (Electronic) Linking ISSN: 00908258 NLM ISO Abbreviation: Gynecol Oncol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 42391853 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Toward precision prognosis: Predicting recurrence-free survival in high-grade serous ovarian cancer patients using multi-time point clinical and computed tomography radiomics data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Roller+L%22">Roller L</searchLink>; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Zhou+N%22">Zhou N</searchLink>; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Atre+I%22">Atre I</searchLink>; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Xiong+N%22">Xiong N</searchLink>; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Li+J%22">Li J</searchLink>; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Cheng+SC%22">Cheng SC</searchLink>; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Liu+N%22">Liu N</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Lacad+D%22">Lacad D</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Adjei+M%22">Adjei M</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Matulonis+UA%22">Matulonis UA</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Konstantinopoulos+PA%22">Konstantinopoulos PA</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Liu+JF%22">Liu JF</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Tayob+N%22">Tayob N</searchLink>; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America.<br /><searchLink fieldCode="AU" term="%22Stover+EH%22">Stover EH</searchLink>; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Medicine, Harvard Medical School, Boston, MA, United States of America. Electronic address: elizabeth&#95;stover@dfci.harvard.edu.<br /><searchLink fieldCode="AU" term="%22Shinagare+AB%22">Shinagare AB</searchLink>; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States of America. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%220365304%22">Gynecologic oncology</searchLink> [Gynecol Oncol] 2026 Jul 02; Vol. 211, pp. 98-107. <i>Date of Electronic Publication: </i>2026 Jul 02. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Academic+Press%22">Academic Press </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0365304 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1095-6859 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200908258%22">00908258 </searchLink><i>NLM ISO Abbreviation: </i>Gynecol Oncol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42391853 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.ygyno.2026.06.007 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 98 Titles: – TitleFull: Toward precision prognosis: Predicting recurrence-free survival in high-grade serous ovarian cancer patients using multi-time point clinical and computed tomography radiomics data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Roller L – PersonEntity: Name: NameFull: Zhou N – PersonEntity: Name: NameFull: Atre I – PersonEntity: Name: NameFull: Xiong N – PersonEntity: Name: NameFull: Li J – PersonEntity: Name: NameFull: Cheng SC – PersonEntity: Name: NameFull: Liu N – PersonEntity: Name: NameFull: Lacad D – PersonEntity: Name: NameFull: Adjei M – PersonEntity: Name: NameFull: Matulonis UA – PersonEntity: Name: NameFull: Konstantinopoulos PA – PersonEntity: Name: NameFull: Liu JF – PersonEntity: Name: NameFull: Tayob N – PersonEntity: Name: NameFull: Stover EH – PersonEntity: Name: NameFull: Shinagare AB IsPartOfRelationships: – BibEntity: Dates: – D: 02 M: 07 Text: 2026 Jul 02 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1095-6859 Numbering: – Type: volume Value: 211 Titles: – TitleFull: Gynecologic oncology Type: main |
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