Academic Journal
Patients’ Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review
| Τίτλος: | Patients’ Perceptions and Attitudes to the Use of Artificial Intelligence in Breast Cancer Diagnosis: A Narrative Review |
|---|---|
| Συγγραφείς: | Pesapane F., Giambersio E., Capetti B., Monzani D., Grasso R., Nicosia L., Rotili A., Sorce A., Meneghetti L., Carriero S., Santicchia S., Carrafiello G., Pravettoni G., Cassano E. |
| Συνεισφορές: | Pesapane F., Giambersio E., Capetti B., Monzani D., Grasso R., Nicosia L., Rotili A., Sorce A., Meneghetti L., Carriero S., Santicchia S., Carrafiello G., Pravettoni G., Cassano E. |
| Στοιχεία εκδότη: | Multidisciplinary Digital Publishing Institute (MDPI) |
| Έτος έκδοσης: | 2024 |
| Συλλογή: | IRIS Università degli Studi di Palermo |
| Θεματικοί όροι: | artificial intelligence, breast cancer, diagnosis, healthcare, policy, population, psychological burden, screening, survey |
| Περιγραφή: | 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. |
| Τύπος εγγράφου: | article in journal/newspaper |
| Γλώσσα: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/38672725; info:eu-repo/semantics/altIdentifier/wos/WOS:001210665600001; volume:14; issue:4; numberofpages:11; journal:LIFE; https://hdl.handle.net/10447/637586 |
| DOI: | 10.3390/life14040454 |
| Διαθεσιμότητα: | https://hdl.handle.net/10447/637586 https://doi.org/10.3390/life14040454 |
| Rights: | info:eu-repo/semantics/openAccess |
| Αριθμός Καταχώρησης: | edsbas.F7078668 |
| Βάση Δεδομένων: | BASE |
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