Abstract
Artificial intelligence (AI) promises to change health care, with some studies showing proof of concept of a provider-level performance in various medical specialties. However, there are many barriers to implementing AI, including patient acceptance and understanding of AI. Patients' attitudes toward AI are not well understood. We systematically reviewed the literature on patient and general public attitudes toward clinical AI (either hypothetical or realised), including quantitative, qualitative, and mixed methods original research articles. We searched biomedical and computational databases from Jan 1, 2000, to Sept 28, 2020, and screened 2590 articles, 23 of which met our inclusion criteria. Studies were heterogeneous regarding the study population, study design, and the field and type of AI under study. Six (26%) studies assessed currently available or soon-to-be available AI tools, whereas 17 (74%) assessed hypothetical or broadly defined AI. The quality of the methods of these studies was mixed, with a frequent issue of selection bias. Overall, patients and the general public conveyed positive attitudes toward AI but had many reservations and preferred human supervision. We summarise our findings in six themes: AI concept, AI acceptability, AI relationship with humans, AI development and implementation, AI strengths and benefits, and AI weaknesses and risks. We suggest guidance for future studies, with the goal of supporting the safe, equitable, and patient-centred implementation of clinical AI.
Highlights
Artificial intelligence (AI), fuelled by advances in deep learning technology and the increasing digitisation of health-care data, shows potential for improving the diagnosis and treatment of many different medical conditions.[1]
We systematically reviewed the literature on attitudes toward clinical AI
Clinical AI was defined as any software made to automate intelligent behaviour in a health-care setting for the purposes of diagnosis or treatment that might be directed towards patients, caregivers, or health-care providers, or a combination
Summary
Artificial intelligence (AI), fuelled by advances in deep learning technology and the increasing digitisation of health-care data, shows potential for improving the diagnosis and treatment of many different medical conditions.[1] For instance, an AI-based tool that diagnoses skin lesions from photos might prompt patients to seek earlier care for melanoma,[2] or an AI tool that analyses electronic health record data might reduce antibiotic resistance by flagging patients being treated in hospital that were inappropriately being given broad-spectrum antibiotics.[3] More broadly, AI has been shown to be able to function to clinicians in medical imaging diagnosis, few studies have been done in realworld clinical environments.[4] at least 64 AI-based medical devices and algorithms have been approved by the US Food & Drug Administration.[5]. There is an emerging body of literature on patients’ attitudes toward AI, but there has been no systematic review on this topic. We systematically reviewed the literature on attitudes toward clinical AI. We summarised current knowledge and offered guidance for future studies, with the ultimate goal of supporting the safe, equitable, and patient-centred implementation of AI in medicine
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