Diagnostic accuracy of artificial intelligence algorithms to predict remove all macroscopic disease and survival rate after complete surgical cytoreduction in patients with ovarian cancer: a systematic review and meta-analysis
Abstract Background Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intelligence (AI) may be more accurate in predic...
Saved in:
Main Authors: | Somayyeh Noei Teymoordash, Hoda Zendehdel, Ali Reza Norouzi, Mahdis Kashian |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-01-01
|
Series: | BMC Surgery |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12893-025-02766-3 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Determining the effect of frailty on survival in advanced ovarian cancer: study protocol for a prospective multicentre national cohort study (FOLERO)
by: Daniel Hunde, et al.
Published: (2025-02-01) -
Clinical efficacy of cytoreductive radical prostatectomy in the treatment of oligometastatic hormone-sensitive prostate cancer
by: Feng Qi, et al.
Published: (2025-01-01) -
Development and validation of a nomogram to predict recurrence in epithelial ovarian cancer using complete blood count and lipid profiles
by: Xi Tang, et al.
Published: (2025-02-01) -
Clinical analysis of different intestinal reconstruction methods after primary cytoreductive surgery combined with rectal resection for advanced ovarian cancer
by: Huimin Wang, et al.
Published: (2025-01-01) -
Role of 18F-PSMA-1007 PET/CT-derived quantitative volumetric tumor parameters in cytoreductive radical prostatectomy selection for patients with low-volume metastatic hormone-sensitive prostate cancer: a retrospective study
by: Junjie Fan, et al.
Published: (2025-02-01)