ReviewCancers2025
Harnessing Artificial Intelligence to Enhance Global Breast Cancer Care: A Scoping Review of Applications, Outcomes, and Challenges.
Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Health Interventions and Psychosocial Outcomes in Women With Breast Cancer: Systematic Review.JMIR cancer · 2026Pooled it
- Side-level versus patient-level evaluation in four-view mammography classification: a comprehensive benchmark on the CMMD dataset.Future science OA · 2026Article
- Patient and Public Perceptions of Artificial Intelligence in Breast Imaging and Clinical Decision-Making: An Exploratory Cross-Sectional Survey Study.Diagnostics (Basel, Switzerland) · 2026Article
- Applications of Artificial Intelligence (AI) in Breast Cancer Care Delivery and Education: A Scoping Review.International journal of environmental research and public health · 2026Article
- Advances in Breast Cancer Diagnostics: From Screening to Precision Medicine.Diagnostics (Basel, Switzerland) · 2026Review
- Breast Cancer Disparities in African and African-Ancestry Populations: Genetics, Epigenetics, Structural Barriers and Technology-Enabled Solutions.British journal of biomedical science · 2026Review
- HER2-Low Breast Cancer at the Interface of Pathology and Technology: Toward Precision Management.Biomedicines · 2025Review
- Artificial intelligence based quantification of T lymphocyte infiltrate predicts prognosis in high grade breast cancer using deep learning and statistical validation.Discover oncology · 2025Article
- The role of AI for improved management of breast cancer: Enhanced diagnosis and health disparity mitigation.Computer methods and programs in biomedicine · 2025Review
- Radiologists' Perspectives on AI Integration in Mammographic Breast Cancer Screening: A Mixed Methods Study.Cancers · 2025Article
- Application of CAD Systems in Breast Cancer Diagnosis Using Machine Learning Techniques: An Overview of Systematic Reviews.Bioengineering (Basel, Switzerland) · 2025Review
- Classification of breast cancer molecular subtypes based on contrast-enhanced ultrasound and superb microvascular imaging using machine learning approach.Gland surgery · 2025Article
- The Underlying Mechanisms and Emerging Strategies to Overcome Resistance in Breast Cancer.Cancers · 2025Review
- Interpretable Machine Learning for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using the Baseline Clinical and Pathological Characteristics.Cancer medicine · 2025Article
- Review
- Article
- Therapeutic Potential of Underexplored Phytoconstituents Targeting Molecular Pathways in Breast Cancer Subtypes.Mini reviews in medicinal chemistry · 2025Review
- Current Strategies to Reducing Interval Breast Cancers: A Systematic Review.Breast cancer (Dove Medical Press) · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years, Artificial Intelligence (AI) has shown transformative potential in advancing breast cancer care globally. This scoping review seeks to provide a comprehensive overview of AI applications in breast cancer care, examining how they could reshape diagnosis, treatment, and management on a worldwide scale and discussing both the benefits and challenges associated with their adoption.
methodsIn accordance with PRISMA-ScR and ensuing guidelines on scoping reviews, PubMed, Web of Science, Cochrane Library, and Embase were systematically searched from inception to end of May 2024. Keywords included "Artificial Intelligence" and "Breast Cancer". Original studies were included based on their focus on AI applications in breast cancer care and narrative synthesis was employed for data extraction and interpretation, with the findings organized into coherent themes.
resultsFinally, 84 articles were included. The majority were conducted in developed countries (
conclusionsAI applications in breast cancer care show promise in enhancing diagnostic accuracy and treatment planning. However, persistent challenges in AI adoption, such as data quality, algorithm transparency, and resource disparities, must be addressed to advance the field.
Indexed as
Identifiers
What 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.