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




AI Helps Hospitals Priorities Patients for Urgent Intensive Care and Ventilator Support

By HospiMedica International staff writers
Posted on 23 Jan 2023
Print article
Image: Researchers have developed an AI-enabled system for prioritizing pneumonia patient treatment (Photo courtesy of Swansea University)
Image: Researchers have developed an AI-enabled system for prioritizing pneumonia patient treatment (Photo courtesy of Swansea University)

Researchers have developed a ‘digital twin’ that can help hospitals to prioritize patients for urgent intensive care and ventilator support. The new innovative system could potentially allow patients to be seen more quickly and receive the most effective treatment based on data from previous pneumonia sufferers.

The three-tiered system developed by a research team at Swansea University (Swansea, UK) uses deep learning methods to build patient-specific digital twins to identify and prioritize critical cases among patients with severe pneumonia. A digital twin is a virtual representation (or computer program) of a real-world physical system or product – it is updated from real-time data, and uses simulation, machine learning and reasoning to aid in decision-making.

“A human digital-twin is a digital replica of a human system or sub-system. This replica is a personalized digital representation, in terms of structure or functioning or both, of an individual or patient’s system,” said Professor Perumal Nithiarasu, Author and Associate Dean for Research, Innovation & Impact in the Faculty of Science & Engineering. “A human digital-twin is a digital replica of a human system or sub-system. This replica is a personalized digital representation, in terms of structure or functioning or both, of an individual or patient’s system. It can provide real-time feedback on how a patient’s health is likely to vary based on their current known condition using periodic input data from the patient’s vitals (such as heart rate, respiration rate).”

“The proposed digital-twin is built on pre-trained deep learning models using data from more than 1895 pneumonia patients. Overall, results indicate that the prediction for ITU and mechanical ventilation prioritization is excellent,” added Professor Nithiarasu. “The data used to train the models is for non-COVID-19 patients with pneumonia. However, this model may be employed in its current form to COVID-19 patients, but transfer learning with COVID-19 patient data will improve the predictions.”

“The COVID-19 pandemic has put an unprecedented stress on an already strained healthcare infrastructure. This situation has forced healthcare providers to prioritize patients in critical need to access ITUs and mechanical ventilation,” explained Dr. Neeraj Kavan Chakshu, Co-Author and IMPACT Fellow. “In the case of COVID-19 (and in other similar forms of influenza), more precise and dynamically evolving system may be necessary to address the sudden increase in severity and the need for mechanical ventilation.”

Related Links:
Swansea University

Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Needlefree Closed System Transfer Device
ChemoClave

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.