eXplainable Artificial Intelligence on Medical Images: A Survey
It provides a review of XAI methods for medical imaging, which is important for clinicians and researchers but is incremental as a survey.
This survey analyzes recent studies in explainable artificial intelligence (XAI) applied to medical diagnosis, addressing the need to explain deep learning model results for diseases like cancers and COVID-19 to facilitate rigorous assessment in medical exams.
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.