Abstract: A waveform annotator system allows clinicians to annotate a physiological data waveform, providing initial annotations based on a model corresponding to a type of the physiological data. The initial annotations may be modified by the clinician as desired. The annotations are saved in an annotation database for later use by the clinician and for training the model using machine learning to improve the initial annotations based on the modifications made by the clinician. The trained model may be distributed to other waveform annotator systems.

Abstract: A system for distributed computing allows researchers performing analysis on data having legal or policy restrictions on movement of the data to perform the analysis on data at multiple sites without exporting the restricted data from each site. A primary system determines which sites contain the data to be executed by a compute job and sends the compute job to the associated site. Resulting calculated data can be exported to a primary collecting and recording system. The system allows the rapid development of analysis code for the compute jobs that can be executed on a local data set then passed to the primary system for distributed machine learning on the multiple sites without any changes to the code of the compute job.

Abstract: A waveform annotator system allows clinicians to annotate a physiological data waveform, providing initial annotations based on a model corresponding to a type of the physiological data. The initial annotations may be modified by the clinician as desired. The annotations are saved in an annotation database for later use by the clinician and for training the model using machine learning to improve the initial annotations based on the modifications made by the clinician. The trained model may be distributed to other waveform annotator systems.

Abstract: A system for distributed computing allows researchers performing analysis on data having legal or policy restrictions on movement of the data to perform the analysis on data at multiple sites without exporting the restricted data from each site. A primary system determines which sites contain the data to be executed by a compute job and sends the compute job to the associated site. Resulting calculated data can be exported to a primary collecting and recording system. The system allows the rapid development of analysis code for the compute jobs that can be executed on a local data set then passed to the primary system for distributed machine learning on the multiple sites without any changes to the code of the compute job.