ReviewCancers2025
Predicting Response to Treatment and Survival in Advanced Ovarian Cancer Using Machine Learning and Radiomics: A Systematic Review.
Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
13 citing papers in PubMed.
- Machine Learning for Radiomics in Oncology: Challenges, Limitations, and Future Directions.Sensors (Basel, Switzerland) · 2026Article
- Current adoption of the Prosthodontic Diagnostic Index for clinical care-A cross-sectional survey study.Journal of prosthodontics : official journal of the American College of Prosthodontists · 2026Article
- Development and validation of a nomogram for predicting recurrence in epithelial ovarian cancer after primary cytoreductive surgery: A single-center retrospective study.Pakistan journal of medical sciences · 2026Article
- Review
- Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention.Journal of ovarian research · 2026Review
- Integration of habitat radiomics and traditional radiomic features for predicting pathological complete response in esophageal squamous cell carcinoma following neoadjuvant immunotherapy and chemotherapy: a multicenter comparative study.Journal of translational medicine · 2026Article
- Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Predicting the early response to neoadjuvant chemotherapy in high-grade serous ovarian cancer by intratumoral habitat heterogeneity based onEuropean journal of nuclear medicine and molecular imaging · 2026Article
- Integrating multi-omics and clinical features to model survival in epithelial ovarian cancer subtypes.Scientific reports · 2025Article
- A Review on Biomarker-Enhanced Machine Learning for Early Diagnosis and Outcome Prediction in Ovarian Cancer Management.Cancer medicine · 2025Review
- Machine Learning Models for Predicting Gynecological Cancers: Advances, Challenges, and Future Directions.Cancers · 2025Review
- Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection.Life (Basel, Switzerland) · 2025Article
- Application of artificial intelligence in gynecologic cancers: A bibliometric analysis.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.