Patients’ Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review

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.

Bridging Discoveries and Treatments: The New Landscape of Breast Cancer Research

“…“Patients’ Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review” synthesizes patient perspectives on the use of artificial intelligence (AI) in breast cancer diagnostics [ 3 ]. It reveals that while there is interest in AI’s potential to improve diagnostic accuracy, there is also significant concern regarding trust and the desire for human oversight in the diagnostic process.…”

“…Welcome to our Special Issue, “Advances in Breast Cancer Research and Treatment” of Life , where we have embarked on a comprehensive exploration of groundbreaking studies that advance our understanding and management of breast cancer. Each paper contributes uniquely to the evolving landscape of breast cancer research, ranging from the clinicopathological characteristics of breast carcinoma with neuroendocrine features [ 1 ], the identification of hub genes in the context of non-alcoholic fatty liver disease and triple-negative breast cancer [ 2 ], to advancements in diagnostic techniques [ 3 ], and the exploration of immunotherapy biomarkers [ 4 ]. Some of the topics covered include innovative methods for breast cancer classification combining transfer learning and attention mechanisms [ 5 ] and the role of diffusion-weighted imaging in breast cancer diagnosis among young patients [ 6 ].…”