https://www.selleckchem.com/products/nd-630.html
Among the three models, random forest model achieved the best performance the accuracy was 84.9% in the leave-one-out cross validation of discovery dataset and 83.6% (sensitivity 81.2%, specificity 84.4%) in the validation dataset. In conclusion, we developed a 10-protein diagnostic panel by the random forest model that was able to distinguish acute appendicitis from confusable acute abdomens with high specificity, which indicated the clinical application potential of noninvasive urinary markers in disease diagnosis. Copyright © 2020 Yin
Like
Comment
Share
