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 …
The promise of digital healthcare technologies
Digital health technologies have been in use for many years in a wide spectrum of
healthcare scenarios. This narrative review outlines the current use and the future strategies …
healthcare scenarios. This narrative review outlines the current use and the future strategies …
Artificial intelligence in ophthalmology: The path to the real-world clinic
Z Li, L Wang, X Wu, J Jiang, W Qiang, H **e… - Cell Reports …, 2023 - cell.com
Artificial intelligence (AI) has great potential to transform healthcare by enhancing the
workflow and productivity of clinicians, enabling existing staff to serve more patients …
workflow and productivity of clinicians, enabling existing staff to serve more patients …
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 …
Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study
Background Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of
prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and …
prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and …
[HTML][HTML] Artificial intelligence and deep learning in ophthalmology: current status and future perspectives
K **, J Ye - Advances in ophthalmology practice and research, 2022 - Elsevier
Background The ophthalmology field was among the first to adopt artificial intelligence (AI)
in medicine. The availability of digitized ocular images and substantial data have made …
in medicine. The availability of digitized ocular images and substantial data have made …