Abstract: In various embodiments, a system for cleaning, marking, and/or interpreting physiological data is disclosed. The system includes a memory having instructions stored thereon, and a processor configured to read the instructions to: receive a training data set comprising physiological data including labeled events corresponding to a predetermined portion of the physiological data, generate a trained artificial intelligence (AI) model configured to identify events within device data, and identify at least one physiological event within a target device data set based on the trained AI model. The trained AI model is generated using an iterative training process based on the training data set.

Abstract: A method of identifying respiratory anomalies includes obtaining respiratory data over a first time period and a second time period that is different than the first time period, identifying at least one type of sound associated with respiration in the respiratory data over the first time period, identifying the at least one type of sound associated with respiration in the respiratory data over the second time period, and identifying abnormal respiration based on a comparison of the at least one type of sound associated with respiration in the respiratory data over the first time period to the at least one type of sound associated with respiration in the respiratory data over the second time period. The at least one type of sound associated with respiration in the respiratory data over the first time period is identified using a first set of features generated by a first processing method.