Jakob GrauslundHenrik Vorum
Published in: Ugeskrift for laeger (2023)
As ophthalmology is an increasingly busy medical specialty relying solidly on imaging technology, this review investigates the introduction of artificial intelligence to improve diagnostic performance and reduce human resources. In diabetic retinopathy screening, algorithms are now regulatory-approved for international markets but not yet tailored for the Danish system. In age-related macular degeneration, algorithms are now able to facilitate the classification and segmentation of disease activity, and in upcoming years, these are likely to assist us to improve diagnosis and provide subsequent clinical care.
Keyphrases
- artificial intelligence
- deep learning
- diabetic retinopathy
- disease activity
- age related macular degeneration
- machine learning
- rheumatoid arthritis
- systemic lupus erythematosus
- healthcare
- rheumatoid arthritis patients
- big data
- convolutional neural network
- ankylosing spondylitis
- endothelial cells
- optical coherence tomography
- juvenile idiopathic arthritis
- high resolution
- palliative care
- induced pluripotent stem cells
- quality improvement
- pain management
- drug administration
- affordable care act
- fluorescence imaging
- chronic pain