Explainable AI (XAI): Core ideas, techniques, and solutions
As our dependence on intelligent machines continues to grow, so does the demand for more
transparent and interpretable models. In addition, the ability to explain the model generally …
transparent and interpretable models. In addition, the ability to explain the model generally …
Explainable artificial intelligence: an analytical review
This paper provides a brief analytical review of the current state‐of‐the‐art in relation to the
explainability of artificial intelligence in the context of recent advances in machine learning …
explainability of artificial intelligence in the context of recent advances in machine learning …
[HTML][HTML] Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
[HTML][HTML] Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: a systematic review
Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …
future potential for transforming almost all aspects of medicine. However, in many …
[HTML][HTML] Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
Medical artificial intelligence (AI) systems have been remarkably successful, even
outperforming human performance at certain tasks. There is no doubt that AI is important to …
outperforming human performance at certain tasks. There is no doubt that AI is important to …
[HTML][HTML] 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 …
and have even outperformed human experts on some of those. However, the black-box …
[HTML][HTML] Key challenges for delivering clinical impact with artificial intelligence
Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …
potential applications being demonstrated across various domains of medicine. However …
[HTML][HTML] Machine learning interpretability: A survey on methods and metrics
DV Carvalho, EM Pereira, JS Cardoso - Electronics, 2019 - mdpi.com
Machine learning systems are becoming increasingly ubiquitous. These systems's adoption
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …
[HTML][HTML] Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare
Precision Medicine implies a deep understanding of inter-individual differences in health
and disease that are due to genetic and environmental factors. To acquire such …
and disease that are due to genetic and environmental factors. To acquire such …
[HTML][HTML] An introductory review of deep learning for prediction models with big data
Deep learning models stand for a new learning paradigm in artificial intelligence (AI) and
machine learning. Recent breakthrough results in image analysis and speech recognition …
machine learning. Recent breakthrough results in image analysis and speech recognition …