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
Sekisui Diagnostics UK Ltd.

Download Mobile App





AI Technology Detects Deterioration in COVID-19 Patients by Identifying Predictive Patterns in Their Vital Signs

By HospiMedica International staff writers
Posted on 11 Aug 2020
Print article
Illustration
Illustration
A new study will apply Artificial Intelligence (AI) technology to look for predictive patterns in the vital signs of COVID-19 patients that could alert the medical team about any deterioration.

The Manchester-based trial is sponsored by The Christie NHS Foundation Trust together with the Manchester University NHS Foundation Trust (MFT) with additional participation from Aptus Clinical and core AI capabilities provided by Zenzium, Ltd. (Cheshire, UK).

The COSMIC-19 (COntinious Signs Monitoring In Covid-19 patients) pilot study aims to recruit 60 inpatients on general wards who are suspected or confirmed to have COVID-19. Approximately 10-20% of hospital inpatients with COVID-19 will need intensive care. The patients on the trial will be monitored for 20 days until either placed on a ventilator or discharged from hospital.

The study will use wireless wearable sensors to automatically collect each patient’s vital signs together with clinical data and observations. Zenzium will then apply its AI technology to look for predictive patterns in the patients’ vital signs that could alert the medical team if the patient is deteriorating. If the prediction indicates that the patient needs critical care, the medical team can intervene earlier to give patients the best chance of recovery. Zenzium’s core technology, including DeepHRV, is based on Deep Learning as applied to time-series measurements and data.

“We are extremely excited to apply our AI technology based on time-series Deep Learning including DeepHRV to this challenge with the potential to make a substantial impact on patient outcomes,” said Anthony D. Bashall, Managing Director & Founder of Zenzium.

“Unfortunately some patients who are suffering from COVID-19 on our hospital wards can become seriously unwell. By using this system, we hope to be able to identify these patients early and this may mean we can optimize their management without the need for them to go to intensive care,” said Professor Fiona Thistlethwaite, medical oncologist at The Christie, who will lead the trial.

Related Links:

Zenzium, Ltd.

Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Gold Member
12-Channel ECG
CM1200B
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Infant Blood Draw Station
Infant Blood Draw Station

Print article

Channels

Surgical Techniques

view channel
Image: LUMISIGHT and Lumicell DVS offer 84% diagnostic accuracy in detecting residual cancer (Photo courtesy of Lumicell)

Cutting-Edge Imaging Platform Detects Residual Breast Cancer Missed During Lumpectomy Surgery

Breast cancer is becoming increasingly common, with statistics indicating that 1 in 8 women will develop the disease in their lifetime. Lumpectomy remains the predominant surgical intervention for treating... 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 Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.