Abstract: A computer implemented system for automatically recording and generating predictive outputs relating to a medical procedure is described. The system is augmented with biometric sensory data from a biometric sensor coupled to a body of a healthcare practitioner. The biometric sensory data is processed to obtain one or more time-synchronized data objects providing a proxy to an estimated stress level associated with the healthcare practitioner, and the one or more time-synchronized data objects are utilized to identify abnormality-related durations of time encapsulated in the form of time-based metadata tags. The time-based metadata tags are utilized to automatically modify characteristics of the recording or generating of predictive outputs to temporarily consume more computational processing resources during the abnormality-related durations of time.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: An improved approach is described herein wherein an automated de-identification system is provided to process the raw captured data. The automated de-identification system utilizes specific machine learning data architectures and transforms the raw captured data into processed captured data by modifying, replacing, or obscuring various identifiable features. The processed captured data can include transformed video or audio data.