AI in health and medicine
Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
[HTML][HTML] A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study
Background There is no simple model to screen for Alzheimer's disease, partly because the
diagnosis of Alzheimer's disease itself is complex—typically involving expensive and …
diagnosis of Alzheimer's disease itself is complex—typically involving expensive and …
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 …
[HTML][HTML] From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare
The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …
advancement has been initiated and shaped by the applications of data-driven, robust, and …
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability
Health data that are publicly available are valuable resources for digital health research.
Several public datasets containing ophthalmological imaging have been frequently used in …
Several public datasets containing ophthalmological imaging have been frequently used in …
Optical coherence tomography angiography in diabetic retinopathy: an updated review
Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus.
Optical coherence tomography angiography (OCTA) has been developed to visualize the …
Optical coherence tomography angiography (OCTA) has been developed to visualize the …
Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms
M AlQuraishi, PK Sorger - Nature methods, 2021 - nature.com
Deep learning using neural networks relies on a class of machine-learnable models
constructed using 'differentiable programs'. These programs can combine mathematical …
constructed using 'differentiable programs'. These programs can combine mathematical …
Artificial intelligence for screening of multiple retinal and optic nerve diseases
Importance The lack of experienced ophthalmologists limits the early diagnosis of retinal
diseases. Artificial intelligence can be an efficient real-time way for screening retinal …
diseases. Artificial intelligence can be an efficient real-time way for screening retinal …
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study
Background Medical artificial intelligence (AI) has entered the clinical implementation
phase, although real-world performance of deep-learning systems (DLSs) for screening …
phase, although real-world performance of deep-learning systems (DLSs) for screening …