Explainable Deep Learning Models in Medical Image Analysis
Deep learning methods have been very effective for a variety of medical diagnostic tasks and have even outperformed human experts on some of those. However, the black-box nature of the algorithms has restricted their clinical use. Recent explainability studies aim to show the features that influence...
Main Authors: | Amitojdeep Singh, Sourya Sengupta, Vasudevan Lakshminarayanan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-06-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/6/6/52 |
Similar Items
-
A Review of Explainable Deep Learning Cancer Detection Models in Medical Imaging
by: Mehmet A. Gulum, et al.
Published: (2021-05-01) -
Information Structures for Causally Explainable Decisions
by: Louis Anthony Cox
Published: (2021-05-01) -
Explaining Deep Learning-Based Traffic Classification Using a Genetic Algorithm
by: Seyoung Ahn, et al.
Published: (2021-01-01) -
Explainable AI: A Review of Machine Learning Interpretability Methods
by: Pantelis Linardatos, et al.
Published: (2021-12-01) -
Machine Learning Interpretability: A Survey on Methods and Metrics
by: Diogo V. Carvalho, et al.
Published: (2019-07-01)