https://www.selleckchem.com/pr....oducts/NVP-BHG712.ht
64%, respectively, using a sensitivity driven variant. By comparison, accuracy, sensitivity, and specificity achieved by board-certified veterinary radiologists was 82.71%, 68.42%, and 87.09%, respectively. Although overall accuracy of the accuracy driven convolutional neural network algorithm and veterinary radiologists was identical, concordance between the two approaches was 85.19%. This study documents proof-of-concept for application of deep learning techniques for computer-aided diagnosis in veterinary medicine.Witteveen-Kolk s
Like
Comment
Share
