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[HTML][HTML] A review of Explainable Artificial Intelligence in healthcare
Abstract Explainable Artificial Intelligence (XAI) encompasses the strategies and
methodologies used in constructing AI systems that enable end-users to comprehend and …
methodologies used in constructing AI systems that enable end-users to comprehend and …
[HTML][HTML] A review on brain tumor segmentation based on deep learning methods with federated learning techniques
Brain tumors have become a severe medical complication in recent years due to their high
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
Interpretability research of deep learning: A literature survey
B Xua, G Yang - Information Fusion, 2024 - Elsevier
Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …
limits people's understanding and trust in its decision-making process. Therefore, it becomes …
Artificial intelligence and explanation: How, why, and when to explain black boxes
Artificial intelligence (AI) is infiltrating nearly all fields of science by storm. One notorious
property that AI algorithms bring is their so-called black box character. In particular, they are …
property that AI algorithms bring is their so-called black box character. In particular, they are …
[HTML][HTML] A sco** review of interpretability and explainability concerning artificial intelligence methods in medical imaging
Abstract Purpose To review eXplainable Artificial Intelligence/(XAI) methods available for
medical imaging/(MI). Method A sco** review was conducted following the Joanna Briggs …
medical imaging/(MI). Method A sco** review was conducted following the Joanna Briggs …
Explainable artificial intelligence: importance, use domains, stages, output shapes, and challenges
There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence
(XAI) approaches to boost people's confidence and trust in Artificial Intelligence methods …
(XAI) approaches to boost people's confidence and trust in Artificial Intelligence methods …
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
Although artificial intelligence (AI) methods hold promise for medical imaging-based
prediction tasks, their integration into medical practice may present a double-edged sword …
prediction tasks, their integration into medical practice may present a double-edged sword …
From admission to discharge: a systematic review of clinical natural language processing along the patient journey
Background Medical text, as part of an electronic health record, is an essential information
source in healthcare. Although natural language processing (NLP) techniques for medical …
source in healthcare. Although natural language processing (NLP) techniques for medical …
Pitfalls in interpretive applications of artificial intelligence in radiology
Interpretive artificial intelligence (AI) tools are poised to change the future of radiology.
However, certain pitfalls may pose particular challenges for optimal AI interpretative …
However, certain pitfalls may pose particular challenges for optimal AI interpretative …
[HTML][HTML] An explainable artificial intelligence model proposed for the prediction of myalgic encephalomyelitis/chronic fatigue syndrome and the identification of …
Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex
and debilitating illness with a significant global prevalence, affecting over 65 million …
and debilitating illness with a significant global prevalence, affecting over 65 million …