“…Detailed descriptions of TSFRESH-based features are provided in the Supporting Information. The F1 score is a weighted measure of model classification capability that accounts for the precision and recall (i.e., the extent of false positives and false negatives) and is widely used to evaluate the performance of machine learning models for biosensing applications. , Precision is a measure of positive predictive value (i.e., false positives), and recall, also known as a true positive rate or sensitivity, is a measure of false negatives. High precision indicates a low number of false positives, and high recall indicates a low number of false negatives.…”