Physionet2018_Challenge_Submission. The code and trained models that were submitted for the official winning entry of the Physionet 2018: You Snooze You Win challenge
Covid19_Respiration. Code to analyze AirGo and other ICU signals data for Covid-19 patients.
ICU-Sleep. Code, Datatables, Tools related to ICU-Sleep trial.
SAH_DCI_Prediction_EEG. The repository contains the implementation for automated prediction of delayed cerebral ischemia after subarachnoid hemorrhage from EEG
SOFA. computing the Sequential Organ Failure Assessment score
icare-dl. Predicting Neurological Outcome in Comatose Patients after Cardiac Arrest with Deep Neural Networks
Rapid_IIIC_Labeling_GUI_MultipleEEGs. GUI for rapid labeling of segments from multiple EEGs, and instructions for preparing data for these labeling tasks
IIIC-IRR. Code to reproduce figures in “Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs”
SOFA-LR. SOFA-LR: a logistic regression based improvement on the SOFA score that accommodates missing data
E-CAM-S. Code and data to accompany “Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S)”
self_similarity. Computing self-similarity for high loop gain and central apnea analysis.
respiratory_event_detection_wearable. This repo contains code, data, and models to detect apnea events from a wearable respiratory band with or without oxygen saturation signals, as described in:
sleep_cognition. predict cognitive function from sleep using deep learning
ecg_respiration_sleep_staging_icu. Repository for “Sleep in the Intensive Care Unit through the Lens of Breathing and Heart Rate Variability: A Cross-Sectional Study”
delphi-deidentification. This is the repository to store all the code related to deidentification using Philter+.
awesome-aws-research. A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources for Academic Researchers new to AWS
bdsp-emr-tools. Tools for extracting EMR data for use in BDSP