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] 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 …
A foundation model for generalizable disease detection from retinal images
Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …
Underspecification presents challenges for credibility in modern machine learning
Machine learning (ML) systems often exhibit unexpectedly poor behavior when they are
deployed in real-world domains. We identify underspecification in ML pipelines as a key …
deployed in real-world domains. We identify underspecification in ML pipelines as a key …
Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective
The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
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 …
Applications of deep learning in fundus images: A review
The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …
importance. Due to its powerful performance, deep learning is becoming more and more …
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study
P Ruamviboonsuk, R Tiwari, R Sayres… - The Lancet Digital …, 2022 - thelancet.com
Background Diabetic retinopathy is a leading cause of preventable blindness, especially in
low-income and middle-income countries (LMICs). Deep-learning systems have the …
low-income and middle-income countries (LMICs). Deep-learning systems have the …
Artificial intelligence in healthcare
Artificial intelligence (AI) is gradually changing medical practice. With recent progress in
digitized data acquisition, machine learning and computing infrastructure, AI applications …
digitized data acquisition, machine learning and computing infrastructure, AI applications …
Machine learning in medicine
Machine Learning in Medicine In this view of the future of medicine, patient–provider
interactions are informed and supported by massive amounts of data from interactions with …
interactions are informed and supported by massive amounts of data from interactions with …