Abstract
Breast cancer is a major global health concern, and early detection is critical for improving patient outcomes. Traditional methods of diagnosis have limitations in accuracy and efficiency, Artificial Intelligence (AI) has the potential to enhance breast cancer diagnosis. However, the successful implementation of AI depends on the knowledge, attitudes and practices of radiologists towards it. This is qualitative study using a selective coding approach to extract learnin our learnings. Radiologists recognized AI's potential benefits but also raised concerns about its accuracy, limitations, and unintended consequences. Results also identified challenges, including trustworthiness of AI, the need for reproducibility and standardized examinations, training requirements, patient acceptance, and financial constraints. The findings emphasize the importance of providing education and training, establishing guidelines and protocols, ensuring transparency, and addressing financial barriers to facilitate the effective adoption of AI in breast cancer diagnosis.
Recommended Citation
Badr, Nabil Georges and Deghaim, Riwa, "Artificial Intelligence Trustworthiness to the Test in Breast Cancer Diagnosis among Lebanese Radiologists" (2024). ITAIS 2024 Proceedings. 37.
https://aisel.aisnet.org/itais2024/37