ReviewLife (Basel, Switzerland)2024
Patients' Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review.
Review in Life (Basel, Switzerland), 2024. 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.
- Artificial intelligence for risk-stratified breast cancer screening: a systematic review of evidence, clinical integration, and ethical implications in risk assessment tools.La Radiologia medica · 2026Pooled it
- Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.The patient · 2025Trial
- Psychometric Evaluation of the Artificial Intelligence Perception Scale for Cancer Patients: A Structural Equation Modeling Approach.Journal of evaluation in clinical practice · 2026Article
- A survey of explainable AI applications in infectious disease diagnosis.BMC infectious diseases · 2026Review
- Patient and Public Perceptions of Artificial Intelligence in Breast Imaging and Clinical Decision-Making: An Exploratory Cross-Sectional Survey Study.Diagnostics (Basel, Switzerland) · 2026Article
- Patient Perspectives on the Use of Artificial Intelligence in Malignant Melanoma Diagnosis.Dermatology practical & conceptual · 2026Article
- Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.Mayo Clinic proceedings. Digital health · 2026Article
- Patient Perspectives on AI-Powered Medical Robots in Breast and Prostate Cancer Care: Qualitative Study.JMIR cancer · 2026Article
- Will AI Replace Physicians in the Near Future? AI Adoption Barriers in Medicine.Diagnostics (Basel, Switzerland) · 2026Review
- Artificial intelligence and breast cancer screening in Serbia: a dual-perspective qualitative study among radiologists and screening-aged women.Frontiers in radiology · 2026Article
- Women's perspectives on integrating artificial intelligence in breast cancer screening services in Abu Dhabi, united Arab Emirates.Scientific reports · 2025Article
- Accessing AI mammography reports impacts patient follow-up behaviors: the unintended consequences of including AI in patient portals.NPJ digital medicine · 2025Article
- Article
- Artificial Intelligence-Driven Personalization in Breast Cancer Screening: From Population Models to Individualized Protocols.Cancers · 2025Review
- Article
- Patients' attitudes toward artificial intelligence (AI) in cancer care: A scoping review protocol.PloS one · 2025Article
- Artificial Intelligence in Breast Cancer Diagnosis and Surgical Decision-Making: An Updated and Comprehensive Overview of Precision and Personalization in Current Evidence.Cancer management and research · 2025Review
- Bridging Discoveries and Treatments: The New Landscape of Breast Cancer Research.Life (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, understanding patient perspectives, particularly considering the psychological impact of breast cancer diagnoses, is crucial. This narrative review synthesizes literature from 2000 to 2023 to examine breast cancer patients' attitudes towards AI in breast imaging, focusing on trust, acceptance, and demographic influences on these views. Methodologically, we employed a systematic literature search across databases such as PubMed, Embase, Medline, and Scopus, selecting studies that provided insights into patients' perceptions of AI in diagnostics. Our review included a sample of seven key studies after rigorous screening, reflecting varied patient trust and acceptance levels towards AI. Overall, we found a clear preference among patients for AI to augment rather than replace the diagnostic process, emphasizing the necessity of radiologists' expertise in conjunction with AI to enhance decision-making accuracy. This paper highlights the importance of aligning AI implementation in clinical settings with patient needs and expectations, emphasizing the need for human interaction in healthcare. Our findings advocate for a model where AI augments the diagnostic process, underlining the necessity for educational efforts to mitigate concerns and enhance patient trust in AI-enhanced diagnostics.
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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.