Survey of Explainable AI Techniques in Healthcare
Guilin University of Electronic Technology · École de Technologie Supérieure · +1 more institution
Abstract
Artificial intelligence (AI) with deep learning models has been widely applied in numerous domains, including medical imaging and healthcare tasks. In the medical field, any judgment or decision is fraught with risk. A doctor will carefully judge whether a patient is sick before forming a reasonable explanation based on the patient's symptoms and/or an examination. Therefore, to be a viable and accepted tool, AI needs to mimic human judgment and interpretation skills. Specifically, explainable AI (XAI) aims to explain the information behind the black-box model of deep learning that reveals how the decisions are made. This paper provides a survey of the most recent XAI techniques used in healthcare and related…
Citation impact
- FWCI
- 85.49
- Percentile
- 100%
- References
- 120
Authors
4Topics & keywords
- Interpretability
- Deep learning
- Categorization
- Health care
- Computer science
- Field (mathematics)
- Artificial intelligence
- Data science
- Peace, Justice and strong institutions