Prediction of response to anti‐vascular endothelial growth factor treatment in diabetic macular oedema using an optical coherence tomography‐based machine learning method
Purpose To predict the anti‐vascular endothelial growth factor (VEGF) therapeutic response of diabetic macular oedema (DME) patients from optical coherence tomography (OCT) at the initiation stage of treatment using a machine learning‐based self‐explainable system. Methods A total of 712 DME patients were included and classified into poor and good responder groups according to central macular thickness decrease after three consecutive injections. Machine learning models were constructed to make predictions based on related features extracted automatically using deep learning algorithms from OCT scans at baseline. Five‐fold cross‐validation was applied to optimize and evaluate the models. The ...
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Zhejiang University
