What are the performance metrics of Deep Neural Network in Biomedical image classification?
Check here for instance:
Article CNN-based Segmentation of Medical Imaging Data
Normally you would like to see the confusion matrix.
Dear Sir,
The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5479722/
https://link.springer.com/content/pdf/bfm%3A978-3-319-42999-1%2F1.pdf
Classification error, kappa coefficient , precision,recall, F-Measure are some performance metrics .
The precision expectation of of Biomedical Image classification must by medical legal standards by best possible. As such, in addition to all you've mentioned, the proper model, real case applications and proper instrumentation are essential.
Usually, medical data is imbalanced. Therefore, the use of the Precision-Recall Curve for performance evaluation would be better.
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