We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App





New AI Technology Helps Hospitals Identify COVID-19 Patients Who Require ICU Treatment

By HospiMedica International staff writers
Posted on 07 Dec 2021
Print article
Illustration
Illustration

New technology could help doctors make the most of limited resources during the COVID-19 pandemic by identifying patients who require intensive care unit (ICU) treatment.

The system, developed by researchers at the University of Waterloo (Waterloo, ON, Canada) and DarwinAI (Waterloo, ON, Canada), an alumni-founded startup company, uses artificial intelligence (AI) to predict the necessity of ICU admission based on more than 200 clinical data points, including vital signs, blood test results and medical history. The new AI software was trained using data from almost 400 cases at Hospital Sirio-Libanes in Sao Paulo, Brazil, in which doctors had decided if COVID patients should be admitted for intensive care.

Based on lessons learned from that known data, the neural network developed by researchers can predict the need for ICU admission in new COVID cases with greater than 95% accuracy. It also identifies the key factors that drive its predictions to help give clinicians confidence in them. Rather than replacing doctors, the technology is meant to arm them with a new tool to make faster, more informed decisions and ensure the patients most in need of intensive care receive it. The researchers have made the technology freely available so engineers and scientists around the world can work to help improve it. They are now incorporating it into a larger clinical decision support system, developed in their ongoing COVID-Net open-source initiative, that also helps doctors detect COVID and determine its severity using AI analysis of medical images.

“That is a very important step in the clinical decision support process for triaging patients and developing treatment plans,” said Alexander Wong, a professor of systems design engineering and Canada Research Chair in AI and Medical Imaging at Waterloo. “The goal is to help clinicians make faster, more consistent decisions based on past patient cases and outcomes. It’s all about augmenting their expertise to optimize the use of medical resources and individualize patient care.”

Related Links:
University of Waterloo 
DarwinAI 

Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Gold Member
12-Channel ECG
CM1200B
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Self-Driving Mobile C-arm
CIARTIC Move

Print article

Channels

Critical Care

view channel
Image: The permeable wearable electronics developed for long-term biosignal monitoring (Photo courtesy of CityUHK)

Super Permeable Wearable Electronics Enable Long-Term Biosignal Monitoring

Wearable electronics have become integral to enhancing health and fitness by offering continuous tracking of physiological signals over extended periods. This monitoring is crucial for understanding an... Read more

Surgical Techniques

view channel
Image: NTT and Olympus have begun the world\'s first joint demonstration experiment of a cloud endoscopy system (Photo courtesy of Olympus)

Cloud Endoscopy System Enables Real-Time Image Processing on the Cloud

Endoscopes, which are flexible tubes inserted into the body's natural openings for internal examination and biopsy collection, are becoming increasingly vital in medical diagnostics. Their minimal invasiveness... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The PATHFAST hs-cTnI-II high-sensitivity troponin assay has been developed for the PATHFAST Biomarker Analyzer (Photo courtesy of Polymedco)

POC Myocardial Infarction Test Delivers Results in 17 Minutes

Chest pain is the second leading cause of emergency department (ED) visits by adults in the United States, generating over 7 million visits annually. In the event of a suspected heart attack, physicians... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.