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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




AI Tool Uses Chest X-Rays to Identify COVID-19 Patients Likely to Develop Life-Threatening Complications with 80% Accuracy

By MedImaging International staff writers
Posted on 13 May 2021
Illustration
Illustration
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80% accuracy which patients with COVID-19 would develop life-threatening complications within four days.

Developed by researchers at NYU Grossman School of Medicine (New York, NY, USA), the program used several hundred gigabytes of data gleaned from 5,224 chest X-rays taken from 2,943 seriously ill patients infected with SARS-CoV-2, the virus behind the infections.

The authors of the study cited the “pressing need” for the ability to quickly predict which patients with COVID-19 are likely to have lethal complications so that treatment resources can best be matched to those at increased risk. For reasons not yet fully understood, the health of some patients with the disease suddenly worsens, requires intensive care, and increases their chances of dying. In a bid to address this need, the NYU Langone team fed not only X-ray information into their computer analysis, but also patients’ age, race, and gender, along with several vital signs and laboratory test results, including weight, body temperature, and blood immune cell levels. Also factored into their mathematical models, which can learn from examples, was the need for a mechanical ventilator and whether each patient survived (2,405) or died (538) from their infections.

Researchers then tested the predictive value of the software tool on 770 chest X-rays from 718 other patients admitted for COVID-19 through the emergency department at NYU Langone hospitals from March 3 to June 28, 2020. The computer program accurately predicted four out of five infected patients who required intensive care and mechanical ventilation and/or died within four days of admission.

A major advantage to machine intelligence programs such as this is that its accuracy can be tracked, updated, and improved with more data. The team plans to add more patient information as it becomes available and is also evaluating what additional clinical test results could be used to improve their test model. As part of further research, the team hopes to soon deploy NYU Langone’s COVID-19 classification test to emergency physicians and radiologists and is working with physicians to draft clinical guidelines for its use.

“Emergency room physicians and radiologists need effective tools like our program to quickly identify those patients with COVID-19 whose condition is most likely to deteriorate quickly so that healthcare providers can monitor them more closely and intervene earlier,” said study co-lead investigator Farah Shamout, PhD, an assistant professor in computer engineering at New York University’s campus in Abu Dhabi.

“We believe that our COVID-19 classification test represents the largest application of artificial intelligence in radiology to address some of the most urgent needs of patients and caregivers during the pandemic,” added Yiqiu “Artie” Shen, MS, a doctoral student at the NYU Center for Data Science.

Related Links:
NYU Grossman School of Medicine

New
Post-Processing Imaging System
DynaCAD Prostate
New
Breast Localization System
MAMMOREP LOOP
Pocket Fetal Doppler
CONTEC10C/CL
Ultrasonic Pocket Doppler
SD1

Channels

Ultrasound

view channel
Image: The new implantable device for chronic pain management is small and flexible (Photo courtesy of The Zhou Lab at USC)

Wireless Chronic Pain Management Device to Reduce Need for Painkillers and Surgery

Chronic pain affects millions of people globally, often leading to long-term disability and dependence on opioid medications, which carry significant risks of side effects and addiction.... Read more

Nuclear Medicine

view channel
Image: The diagnostic tool could improve diagnosis and treatment decisions for patients with chronic lung infections (Photo courtesy of SNMMI)

Novel Bacteria-Specific PET Imaging Approach Detects Hard-To-Diagnose Lung Infections

Mycobacteroides abscessus is a rapidly growing mycobacteria that primarily affects immunocompromised patients and those with underlying lung diseases, such as cystic fibrosis or chronic obstructive pulmonary... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.