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 …

The ambition of precision medicine is to design and optimize the pathway for diagnosis,
therapeutic intervention, and prognosis by using large multidimensional biological datasets …

Purpose To develop and validate a deep learning system for diabetic retinopathy (DR)
grading based on fundus fluorescein angiography (FFA) images. Methods A total of 11,214 …

Artificial intelligence (AI) assistants for clinical decision making show increasing promise in
medicine. However, medical assessments can be contentious, leading to expert …

Medical data labeling workflows critically depend on accurate assessments from human
experts. Yet human assessments can vary markedly, even among medical experts. Prior …

Objective. To evaluate diabetic retinopathy (DR) screening via deep learning (DL) and
trained human graders (HG) in a longitudinal cohort, as case spectrum shifts based on …

Diabetic retinopathy is a complication of diabetes mellitus. Its early diagnosis can prevent its
progression and avoid the development of other major complications such as blindness …