https://www.selleckchem.com/pr....oducts/k-ras-g12c-in
The augmented training data set consisted of 80 672 images. Their distribution was 38% PA, 35% lateral, and 27% oblique projections. When evaluated on the test data set, the model performed with overall 96.0% accuracy, 93.6% precision, 93.6% sensitivity, and 97.1% specificity. Radiographic positioning of hand X-rays can be effectively classified by a deep neural network. Further work will be performed on localization of abnormalities, automated assessment of standard radiographic measures and eventually on computer-aided
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