mlsanityData to 7 Oct 2026

eXplainable Artificial Intelligence on Medical Images: A Survey

arXiv 2305.07511 ↗First posted 12 May 2023cs.LG cs.AI cs.CYcited by 0

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Abstract (arXiv)

Over the last few years, the number of works about deep learning applied to the medical field has increased enormously. The necessity of a rigorous assessment of these models is required to explain these results to all people involved in medical exams. A recent field in the machine learning area is explainable artificial intelligence, also known as XAI, which targets to explain the results of such black box models to permit the desired assessment. This survey analyses several recent studies in the XAI field applied to medical diagnosis research, allowing some explainability of the machine learning results in several different diseases, such as cancers and COVID-19.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 48 of its 133 references that are in the map. First posted on arXiv 12 May 2023.

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48 of 133 references.

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