[HTML][HTML] Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
[HTML][HTML] Large language models encode clinical knowledge
Large language models (LLMs) have demonstrated impressive capabilities, but the bar for
clinical applications is high. Attempts to assess the clinical knowledge of models typically …
clinical applications is high. Attempts to assess the clinical knowledge of models typically …
Large language models encode clinical knowledge
Large language models (LLMs) have demonstrated impressive capabilities in natural
language understanding and generation, but the quality bar for medical and clinical …
language understanding and generation, but the quality bar for medical and clinical …
[HTML][HTML] Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
[HTML][HTML] 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 …
[HTML][HTML] An overview of artificial intelligence in diabetic retinopathy and other ocular diseases
Artificial intelligence (AI), also known as machine intelligence, is a branch of science that
empowers machines using human intelligence. AI refers to the technology of rendering …
empowers machines using human intelligence. AI refers to the technology of rendering …
[HTML][HTML] Predicting the risk of developing diabetic retinopathy using deep learning
Background Diabetic retinopathy screening is instrumental to preventing blindness, but
scaling up screening is challenging because of the increasing number of patients with all …
scaling up screening is challenging because of the increasing number of patients with all …
[HTML][HTML] Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology
The COVID-19 pandemic has resulted in massive disruptions within health care, both
directly as a result of the infectious disease outbreak, and indirectly because of public health …
directly as a result of the infectious disease outbreak, and indirectly because of public health …
[HTML][HTML] Trustworthy AI: closing the gap between development and integration of AI systems in ophthalmic practice
C González-Gonzalo, EF Thee, CCW Klaver… - Progress in retinal and …, 2022 - Elsevier
An increasing number of artificial intelligence (AI) systems are being proposed in
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …