Survey of explainable AI techniques in healthcare
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 …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
What is human-centered about human-centered AI? A map of the research landscape
T Capel, M Brereton - Proceedings of the 2023 CHI conference on …, 2023 - dl.acm.org
The application of Artificial Intelligence (AI) across a wide range of domains comes with both
high expectations of its benefits and dire predictions of misuse. While AI systems have …
high expectations of its benefits and dire predictions of misuse. While AI systems have …
[HTML][HTML] Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research
The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns
regarding explainability. Recent studies have discussed the emerging demand for …
regarding explainability. Recent studies have discussed the emerging demand for …
Modeling adoption of intelligent agents in medical imaging
Artificial intelligence has the potential to transform many application domains fundamentally.
One notable example is clinical radiology. A growing number of decision-making support …
One notable example is clinical radiology. A growing number of decision-making support …
Explainability and causability in digital pathology
The current move towards digital pathology enables pathologists to use artificial intelligence
(AI)‐based computer programmes for the advanced analysis of whole slide images …
(AI)‐based computer programmes for the advanced analysis of whole slide images …
[HTML][HTML] Explainability and causability for artificial intelligence-supported medical image analysis in the context of the European In Vitro Diagnostic Regulation
Artificial Intelligence (AI) for the biomedical domain is gaining significant interest and holds
considerable potential for the future of healthcare, particularly also in the context of in vitro …
considerable potential for the future of healthcare, particularly also in the context of in vitro …
[HTML][HTML] Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis
In this paper, we study human–AI collaboration protocols, a design-oriented construct aimed
at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We …
at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We …
Human-in-the-loop reinforcement learning: A survey and position on requirements, challenges, and opportunities
Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to
enable agents to learn and perform tasks autonomously with superhuman performance …
enable agents to learn and perform tasks autonomously with superhuman performance …
Why do errors arise in artificial intelligence diagnostic tools in histopathology and how can we minimize them?
H Evans, D Snead - Histopathology, 2024 - Wiley Online Library
Artificial intelligence (AI)‐based diagnostic tools can offer numerous benefits to the field of
histopathology, including improved diagnostic accuracy, efficiency and productivity. As a …
histopathology, including improved diagnostic accuracy, efficiency and productivity. As a …
[HTML][HTML] Assessing the communication gap between AI models and healthcare professionals: Explainability, utility and trust in AI-driven clinical decision-making
This paper contributes with a pragmatic evaluation framework for explainable Machine
Learning (ML) models for clinical decision support. The study revealed a more nuanced role …
Learning (ML) models for clinical decision support. The study revealed a more nuanced role …