Andrew Chung, Qiushi Chen, William Curry, Todd Felix, Wen-Jan Tuan
Breast Cancer Screening During the COVID-19 Pandemic in the United States: Results From Real-World Health Records Data
Annals of family medicine
current research aims generate alternative model classical methods determination subclinical mastitis 4 levels healthy suspicious subclinical clinical purpose multilayer perceptron mlp artificial neural networks ann developed test model 5 variables physical properties milk somatic cell count scc electrical conductivity ec ph density temperature fore milking tfm included model classification mastitis model performance validated test data 25 compared multinomial logistic regression mnlr mlp model shown satisfactory performance accuracy 9514 141 aic score better control model mnlr 8027 133 aic despite using higher number parameters 104 since main problem diagnose subclinical mastitis cause visible symptoms important distinguish absolute subclinical suspicious excluded positives absolute healthy suspicious included positives ones therefore optimum cutoff threshold evaluated two different scenarios variable scc gold standard indicator subclinical mastitis results compared interpretation model performance results show 5variable mlp model exhibits high sensitivity 9322 auc 095 healthy ones low cutoff thresholds well new studies provide better understanding evaluating economics sustainability animal welfare health aspects together determine optimal threshold value