https://www.selleckchem.com/btk.html
902 (MobileNetV2), followed by 0.745 (Inception-Resnet-V2), 0.731 (ResNet-5, and 0.636 (Inception-V3). Accuracy ranged between 0.73-0.77, sensitivity 0.72-0.88, specificity 0.58-0.84, PPV 0.68-0.81, and NPV 0.73-0.83. Macro-AUC-ROC for MobileNetV2 based multiclass-classifier was 0.91, with accuracy of 66%. Binary and multiclass-classifier models based on MobileNetV2 were loaded onto a publicly accessible and user-friendly website (https//headneckml.com/tympanic). This allows the readership to upload TM images for real-time predictions using the de
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