ReviewCureus2022
Artificial Intelligence in Breast Cancer Screening and Diagnosis.
Review in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- The dark matter in cancer immunology: beyond the visible- unveiling multiomics pathways to breakthrough therapies.Journal of translational medicine · 2025Review
- Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data.Cancer reports (Hoboken, N.J.) · 2025Article
- Artificial Intelligence and Early Detection of Breast, Lung, and Colon Cancer: A Narrative Review.Cureus · 2025Review
- Application of ultrasound in combination with other methods in gynecological disease: artificial intelligence, surgery, and drugs.Frontiers in oncology · 2025Review
- Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.Virchows Archiv : an international journal of pathology · 2024Review
- Deep learning radiomics based on multimodal imaging for distinguishing benign and malignant breast tumours.Frontiers in medicine · 2024Article
- Empowering precision medicine: regenerative AI in breast cancer.Frontiers in oncology · 2024Article
- Review
- A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection.Cureus · 2023Review
- Exploring the human microbiome - A step forward for precision medicine in breast cancer.Cancer reports (Hoboken, N.J.) · 2023Review
- Review
- Use of Artificial Intelligence in the Advancement of Breast Surgery and Implications for Breast Reconstruction: A Narrative Review.Journal of clinical medicine · 2023Review
- The Systematic Review of Artificial Intelligence Applications in Breast Cancer Diagnosis.Diagnostics (Basel, Switzerland) · 2022Review
- Editorial: Diagnosis and Treatment of Breast Cancer in 2022: The Rise of Novel Molecular Biomarkers.Frontiers in molecular biosciences · 2022Article
- Pathology in the artificial intelligence era: Guiding innovation and implementation to preserve human insight.Academic pathologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a disease that continues to plague our modern society. Among all types of cancer, breast cancer is now the most common type of cancer occurring in women worldwide. Various factors, including genetics, lifestyle, and the environment, have contributed to the rise in the prevalence of breast cancer among women of all socioeconomic strata. Therefore, proper screening for early diagnosis and treatment becomes a major factor when fighting the disease. Artificial intelligence (AI) continues to revolutionize various spheres of our lives with its numerous applications. Using AI in the existing screening process makes obtaining results even easier and more convenient. Faster, more accurate results are some of the benefits of AI methods in breast cancer screening. Nonetheless, there are many challenges in the process of the integration of AI that needs to be addressed systematically. The following is a review of the application of AI in breast cancer screening.
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.