[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …
grows, especially in high-stakes decision making areas such as medical image analysis …
[HTML][HTML] Transparency of deep neural networks for medical image analysis: A review of interpretability methods
Artificial Intelligence (AI) has emerged as a useful aid in numerous clinical applications for
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
diagnosis and treatment decisions. Deep neural networks have shown the same or better …
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Concept bottleneck models
We seek to learn models that we can interact with using high-level concepts: if the model did
not think there was a bone spur in the x-ray, would it still predict severe arthritis? State-of-the …
not think there was a bone spur in the x-ray, would it still predict severe arthritis? State-of-the …
Acquisition of chess knowledge in alphazero
We analyze the knowledge acquired by AlphaZero, a neural network engine that learns
chess solely by playing against itself yet becomes capable of outperforming human chess …
chess solely by playing against itself yet becomes capable of outperforming human chess …
Explainable AI methods-a brief overview
Abstract Explainable Artificial Intelligence (xAI) is an established field with a vibrant
community that has developed a variety of very successful approaches to explain and …
community that has developed a variety of very successful approaches to explain and …
A review on explainable artificial intelligence for healthcare: why, how, and when?
S Bharati, MRH Mondal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …
medicine. Concerns have been raised about the explainability of the decisions that are …
A survey on the interpretability of deep learning in medical diagnosis
Q Teng, Z Liu, Y Song, K Han, Y Lu - Multimedia Systems, 2022 - Springer
Deep learning has demonstrated remarkable performance in the medical domain, with
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
Concept activation regions: A generalized framework for concept-based explanations
J Crabbé, M van der Schaar - Advances in Neural …, 2022 - proceedings.neurips.cc
Abstract Concept-based explanations permit to understand the predictions of a deep neural
network (DNN) through the lens of concepts specified by users. Existing methods assume …
network (DNN) through the lens of concepts specified by users. Existing methods assume …
Survey on explainable AI: From approaches, limitations and applications aspects
In recent years, artificial intelligence (AI) technology has been used in most if not all domains
and has greatly benefited our lives. While AI can accurately extract critical features and …
and has greatly benefited our lives. While AI can accurately extract critical features and …