Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
[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 …
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
[HTML][HTML] A systematic review of Explainable Artificial Intelligence models and applications: Recent developments and future trends
A Saranya, R Subhashini - Decision analytics journal, 2023 - Elsevier
Artificial Intelligence (AI) uses systems and machines to simulate human intelligence and
solve common real-world problems. Machine learning and deep learning are Artificial …
solve common real-world problems. Machine learning and deep learning are Artificial …
Artificial intelligence in healthcare: review, ethics, trust challenges & future research directions
The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …
diagnosis with their outstanding image classification performance. In spite of the outstanding …
Opportunities and challenges in explainable artificial intelligence (xai): A survey
Nowadays, deep neural networks are widely used in mission critical systems such as
healthcare, self-driving vehicles, and military which have direct impact on human lives …
healthcare, self-driving vehicles, and military which have direct impact on human lives …
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 …
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 …
Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks
LP Cen, J Ji, JW Lin, ST Ju, HJ Lin, TP Li… - Nature …, 2021 - nature.com
Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses
and appropriate treatments. Single disease-based deep learning algorithms had been …
and appropriate treatments. Single disease-based deep learning algorithms had been …