Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks

• Published in: Computers in biology and medicine Vol. 156; no. C; p. 106668
• Main Authors: Nazir, Sajid, Dickson, Diane M., Akram, Muhammad Usman
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.04.2023; Elsevier Limited; Elsevier
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Autonomous cars; Backpropagation; Blackbox; Brain; Classification; Clinical medicine; Coronaviruses; COVID-19; Decision making; Deep learning; Diagnosis; Diagnostic Imaging; Disease; Explainable artificial intelligence; Features; Humans; Image classification; Internal Medicine; Interpretable AI; Learning algorithms; Machine Learning; Medical diagnosis; Medical electronics; Medical imaging; Neural networks; Neural Networks, Computer; Other; Patients; Predictions; Predictive models; Subject specialists; Supervised learning; Surveys; Backpropagation; Blackbox; Supervised learning; Neural networks; Predictive models; Features; Diagnostic imaging; Interpretable AI
• ISSN: 0010-4825; 1879-0534; 1879-0534
• DOI: 10.1016/j.compbiomed.2023.106668

Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease diagnosis with their outstanding image classification performance. In spite of the outstanding results, the widespread adoption of these techniques in clinical practice is still taking place at a moderate pace....