Resources
6 results for "sepsis"
Challenge
Open Access
Early Prediction of Sepsis from Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019
Sepsis is a life-threatening condition that occurs when the body's response to infection causes tissue damage, organ failure, or death (Singer et al., 2016). In the U.S., nearly 1.7 million people develop sepsis and 270,000 people die from sepsis ea…
Database
Contributor Review
Chest Computed Tomography for patients with sepsis in the Emergency Department
Sepsis is a systematic inflammatory response syndrome that can impact all vital organs. Lung is the most commonly involved organ that sepsis can cause lung injury. Lung injury can have a variety clinical presentations and can be captured by chest im…
Database
Credentialed Access
Clinical Time Series Datasets for Trajectory Flow Matching Evaluation: ICU Sepsis, ICU Cardiac Arrest, and ICU GIB Cohorts
This resource comprises three clinical time series datasets used in the paper Trajectory Flow Matching with Applications to Clinical Time Series Modeling to evaluate models for handling irregularly sampled data in critical care settings. The ICU Sep…
Database
Credentialed Access
Synthetic Acute Hypotension and Sepsis Datasets Based on MIMIC-III and Published as Part of the Health Gym Project
These two synthetic datasets comprise vital signs, laboratory test results, administered fluid boluses and vasopressors for 3,910 patients with acute hypotension and for 2,164 patients with sepsis in the Intensive Care Unit (ICU). The patient cohort…
Database
Credentialed Access
TherLid: A Thermometry Linked Dataset
A recent study showed that infrared (IR) sensors may be prone to calibration discrepancies among darker-pigmented patients. Similar disparities have already been verified in pulse oximetry. This raises questions about whether thermometry measurement…
Database
Credentialed Access
Critical care database comprising patients with infection at Zigong Fourth People's Hospital
Patients treated in the intensive care unit (ICU) are closely monitored and receive intensive treatment. Such aggressive monitoring and treatment will generate high-granularity data from both electronic healthcare records and nursing chart. These da…