Shweta Narkar, Yunfeng Zhang, et al.
IUI 2021
Results of radiology imaging studies are not typically comprehensible to patients. With the advances in artificial intelligence (AI) technology in recent years, it is expected that AI technology can aid patients’ understanding of radiology imaging data. The aim of this study is to understand patients’ perceptions and acceptance of using AI technology to interpret their radiology reports. We conducted semi-structured interviews with 13 participants to elicit reflections pertaining to the use of AI technology in radiology report interpretation. A thematic analysis approach was employed to analyze the interview data. Participants have a generally positive attitude toward using AI-based systems to comprehend their radiology reports. AI is perceived to be particularly useful in seeking actionable information, confirming the doctor’s opinions, and preparing for the consultation. However, we also found various concerns related to the use of AI in this context, such as cyber-security, accuracy, and lack of empathy. Our results highlight the necessity of providing AI explanations to promote people’s trust and acceptance of AI. Designers of patient-centered AI systems should employ user-centered design approaches to address patients’ concerns. Such systems should also be designed to promote trust and deliver concerning health results in an empathetic manner to optimize the user experience.
Shweta Narkar, Yunfeng Zhang, et al.
IUI 2021
Bingsheng Yao, Prithviraj Sen, et al.
ACL 2023
Abraham Sanders, Tomek Strzalkowski, et al.
NAACL 2022
Nitesh Goyal, Sungsoo Ray Hong, et al.
IUI 2023