Classification of diabetic maculopathy based on optical coherence tomography images using a Vision Transformer model.
Liwei CaiChi WenJingwen JiangCongbi LiangHongmei ZhengYu SuChangzheng ChenPublished in: BMJ open ophthalmology (2023)
Our DL model based on Vision Transformer demonstrated a relatively high accuracy in the detection of OCT grading of DM, which can help with patients in a preliminary screening to identify groups with serious conditions. These patients need a further test for an accurate diagnosis, and a timely treatment to obtain a good visual prognosis. These results emphasised the potential of artificial intelligence in assisting clinicians in developing therapeutic strategies with DM in the future.
Keyphrases
- artificial intelligence
- end stage renal disease
- optical coherence tomography
- deep learning
- machine learning
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- type diabetes
- palliative care
- big data
- metabolic syndrome
- high resolution
- mass spectrometry
- adipose tissue
- current status
- climate change
- replacement therapy
- wound healing
- quantum dots