ReviewFrontiers in oncology2024
A contemporary review of breast cancer risk factors and the role of artificial intelligence.
Review in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An updated systematic review with meta-analysis and meta-regression of the factors associated with human visceral leishmaniasis in the Americas.Infectious diseases of poverty · 2025Pooled it
- Senescent obesity signature in breast cancer: a paradigm of reverse cardio-oncology.European heart journal · 2026Review
- Exploring Traditional Breast Cancer Risk Genes Among Aboriginal and Torres Strait Islander Women.Life (Basel, Switzerland) · 2026Article
- Regulatory Variants in the KRAS 3'UTR and Intron 2 Are Associated with Breast Cancer Susceptibility Through Independent and Combinatorial Effects in a Mexican Population.Biomedicines · 2026Article
- Review
- The Immunoregulatory Roles of ERα in Breast Cancer: Mechanisms, Crosstalk, and Therapeutic Insights.Journal of cancer prevention · 2026Review
- Cosmetic Habits Associated With Breast Cancer in Benin: A Multicenter Case-Control Study.Journal of cosmetic dermatology · 2026Article
- Epidemiological Landscape of Breast Cancer in Northern India: A Narrative Review of Jammu and Kashmir.Cureus · 2026Review
- Inhibitory Effect of Progesterone on Breast Cancer Progression and Migration via the Regulation of Epithelial-Mesenchymal Transition.Oncology research · 2026Article
- The Underlying Mechanisms and Emerging Strategies to Overcome Resistance in Breast Cancer.Cancers · 2025Review
- Article
- The times they are AI-changing: AI-powered advances in the application of extracellular vesicles to liquid biopsy in breast cancer.Extracellular vesicles and circulating nucleic acids · 2025Review
- Application of ultrasound in combination with other methods in gynecological disease: artificial intelligence, surgery, and drugs.Frontiers in oncology · 2025Review
- Association Between Emphysema and Breast Cancer: Data from National Health and Nutrition Examination Survey (1998-2016).Women's health reports (New Rochelle, N.Y.) · 2025Article
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast cancer continues to be a significant global health issue, necessitating advancements in prevention and early detection strategies. This review aims to assess and synthesize research conducted from 2020 to the present, focusing on breast cancer risk factors, including genetic, lifestyle, and environmental aspects, as well as the innovative role of artificial intelligence (AI) in prediction and diagnostics. Methods: A comprehensive literature search, covering studies from 2020 to the present, was conducted to evaluate the diversity of breast cancer risk factors and the latest advances in Artificial Intelligence (AI) in this field. The review prioritized high-quality peer-reviewed research articles and meta-analyses. Results: Our analysis reveals a complex interplay of genetic, lifestyle, and environmental risk factors for breast cancer, with significant variability across different populations. Furthermore, AI has emerged as a promising tool in enhancing the accuracy of breast cancer risk prediction and the personalization of prevention strategies. Conclusion: The review highlights the necessity for personalized breast cancer prevention and detection approaches that account for individual risk factor profiles. It underscores the potential of AI to revolutionize these strategies, offering clear recommendations for future research directions and clinical practice improvements.
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.