ReviewCurrent treatment options in oncology2025
The Evolving Landscape of Ovarian Cancer: Innovations in Biotechnology and Artificial Intelligence- Based Screening and Treatment.
Review in Current treatment options in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis 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
4 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
- A bibliometric analysis of artificial intelligence in ovarian cancer research from 2006 to 2025.Discover oncology · 2026Article
- Ensemble machine learning algorithms leveraged on serum proteomics for enhanced early detection of ovarian cancer.Scientific reports · 2026Article
- Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention.Journal of ovarian research · 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
4 authors.
Funding
Abstract
opinion statementOvarian Cancer (OC) is a serious health problem that affects a great number of women globally. It is still one of the deadliest gynecological cancers due to restricted treatment choices and late-stage diagnosis. Worldwide, OC ranks as the seventh most commonly diagnosed kind of malignant neoplasm in women and the eighth leading cause of death in them. Because of several reasons such as genetic and economic ones, the epidemiology of OC shows disparities between races and countries. Lack of public screening program makes it difficult to diagnose this cancer earlier and as a result, most OCs are detected after they have progressed to other parts. However, advances in biotechnology and artificial intelligence (AI) are transforming both early detection and treatment strategies. Over the years, the application of AI in OC screening has shown promising results. The best way to get the drawbacks of traditional treatment methods is to combine newly developed strategies with existing treatment choices. Additionally, clinical researches are crucial to ensure the practical implementation of these advancements in healthcare settings. Utilizing state-of-the-art technologies and creative strategies will offer significant opportunity to lessen the worldwide impact of this curable cancer thereby enhancing women's quality of life in low and middle income countries (LMICs) and beyond. Hence, this review explores recent breakthroughs in ovarian cancer screening and therapy, highlighting the synergistic role of biotechnology and AI in improving patient outcomes that reshapes the ovarian cancer treatment landscape.
Indexed as
Identifiers
40489020What OpenQuestion 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 OpenQuestion graph.