ReviewOncology reports2024
Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review).
Review in Oncology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in ovarian pathophysiology and management: a systematic review and meta-analysis.Journal of ovarian research · 2026Pooled it
- Ovarian cancer staging and follow-up: updated guidelines from the European Society of Urogenital Radiology female pelvic imaging working group.European radiology · 2025Guideline
- Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook.Frontiers in oncology · 2025Pooled it
- A bibliometric analysis of artificial intelligence in ovarian cancer research from 2006 to 2025.Discover oncology · 2026Article
- Navigating Hope and Illness Cognition in Advanced Ovarian Cancer Patients: A CSM-Based Phenomenological Study.Psycho-oncology · 2026Article
- Evaluating Performance of a Deep Learning-based Artificial Intelligence Model for Ovarian Tumor Classification Using a Multicenter CT Dataset.Radiology. Imaging cancer · 2026Article
- Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer.NPJ digital medicine · 2026Review
- Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention.Journal of ovarian research · 2026Review
- Role of Imaging Techniques in Ovarian Cancer Diagnosis: Current Approaches and Future Directions.Cancers · 2026Review
- Applications of artificial intelligence and machine learning models in the prognosis and diagnosis of ovarian cancer.Frontiers in oncology · 2026Review
- AI-driven radiogenomics in gynecologic oncology: from radiological digital biopsy to a new paradigm in precision therapy.Frontiers in oncology · 2026Review
- Advances in the use of exosomes for the diagnosis and treatment of ovarian cancer.World journal of surgical oncology · 2025Review
- RNA sequencing in ovarian cancer research: a comprehensive review.Journal of ovarian research · 2025Review
- Fibrinolysis markers as predictive indicators of neoadjuvant chemotherapy efficacy in ovarian cancer patients.Future oncology (London, England) · 2025Article
- Isoquercitrin triggers the ferroptosis of ovarian cancer via SLC7A11-dependent manner to repress its tumorigenesis.Discover oncology · 2025Article
- Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications.Translational oncology · 2025Article
- Early prediction and risk stratification of ovarian cancer based on clinical data using machine learning approaches.Journal of gynecologic oncology · 2025Article
- Ovarian Cancer: Multi-Omics Data Integration.International journal of molecular sciences · 2025Review
- A nomogram combining clinical features, O-RADS US, and radiomics based on ultrasound imaging for diagnosing ovarian cancer.Scientific reports · 2025Article
- Artificial Intelligence and Novel Technologies for the Diagnosis of Upper Tract Urothelial Carcinoma.Medicina (Kaunas, Lithuania) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.
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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.