ReviewFrontiers in medicine2025
Artificial intelligence for precision management of epithelial ovarian cancer: a comprehensive review.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in ovarian pathophysiology and management: a systematic review and meta-analysis.Journal of ovarian research · 2026Pooled it
- The use of MRI in the diagnosis of ovarian cancer.Frontiers in medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epithelial ovarian cancer (EOC) has a high rate of incidence and mortality, seriously threatening women's health. Artificial intelligence (AI) possesses functions such as image recognition, data mining and pattern recognition, which can solve problems that traditional statistical methods cannot handle, such as large amounts of data and data missing. It has achieved breakthrough progress in the fields of risk prediction, diagnosis, treatment and response assessment of malignant tumors. Most AI technologies are mainly applied in the preoperative diagnosis of EOC, as well as in imaging and pathological genomics. However, their application in treatment and prognosis assessment studies is relatively limited. This article reviews the AI application in the treatment and prognosis assessment of EOC in recent years, including the establishment of prediction models for complete cytoreduction (R0 resection), the prediction of chemotherapy and targeted drug efficacy, and the application of different AI technologies based on pathology, radiomics, and clinical data for the prognosis assessment of EOC, with the aim of providing more ideas for the application of AI in EOC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.