The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review

In domains such as medical and healthcare, the interpretability and explainability of machine learning and artificial intelligence systems are crucial for building trust in their results. Errors caused by these systems, such as incorrect diagnoses or treatments, can have severe and even life-threatening consequences for patients. To address this issue, Explainable Artificial Intelligence (XAI) has emerged as a popular area of research, focused on understanding the black-box nature of complex and hard-to-interpret machine learning models. While humans can increase the accuracy of these models through technical expertise, understanding how these models actually function during training can be difficult or even…

• NT
  Norges Teknisk-Naturvitenskapelige Universitet
• DF
  Direktoratet for internasjonalisering og kvalitetsutvikling i høgare utdanning

  Award: NORPART-2021/10502