Big Data Cogn. Comput., Volume 8, Issue 7 (July 2024) – 10 articles
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Interest and engagement with trustworthy AI in healthcare are rising, as shown by its growing use in diagnostics and patient management. However, translating theoretical frameworks into actual practices remains limited, evidenced by a few dedicated papers. The present study reports the first scoping review on the topic that is specific to decision-making systems in the biomedical domain and attempts to consolidate existing practices as they appear in the academic literature on the subject. The main findings show how the implementation of trustworthy AI principles is inconsistent, particularly in explainability, technical robustness, safety, privacy, and human oversight. This highlights the need for a more comprehensive and integrated approach to trustworthy AI in healthcare. View this paper
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