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Author: Rasheed, Qayyum, Ghaly, Razi, & Qadir
Publisher: ScienceDirect
Year: 2022
Summary: This article discusses and addresses the main questions being asked about the liability, trust, and interpretability of using Machine Learning (ML) and Deep Learning (DL) models in healthcare. Additionally, many challenges faced in ML include security, safety, and robustness. Despite these questions and challenges, ML and DL models have been utilized in healthcare for tasks such as image reconstruction, electronic health record management, disease prediction, and many more applications. Since these models typically possess a black-box nature, it is important to ensure that they are interpretable and explainable to establish trust with clinicians and patients.