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


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

AI Algorithm Predicts Chronic Conditions from CT Scans

By HospiMedica International staff writers
Posted on 17 Dec 2018
Print article
Image: AI algorithms can help identify early evidence of disease (Photo courtesy of Zebra Medical Imaging).
Image: AI algorithms can help identify early evidence of disease (Photo courtesy of Zebra Medical Imaging).
Artificial intelligence (AI) algorithms can take advantage of existing computed tomography (CT) data to identify patients at risk of osteoporotic fractures and cardiovascular disease (CVD).

The algorithms, developed by Zebra Medical Vision (Shefayim, Israel), are based on anonymized databases of medical images and clinical data that were used to train them to discover chronic diseases by automated imaging analysis. The Zebra algorithm engine can be deployed in both cloud and on-site configurations, and is designed to integrate into picture archiving and communication systems (PACS), radiological information systems (RIS), and electronic medical record (EMR) systems.

Two recent studies undertaken by Clalit Health Services (Tel Aviv, Israel), which owns and operates 1,500 primary care clinics and 14 hospitals in Israel, treating over 4 million patients, validated that the algorithms can successfully predict osteoporotic fractures and CVD. The first study involved a retrospective analysis of 48,227patients with abdominal CTs, in order to identify radiologic risk markers of major and hip-specific osteoporotic fractures. The results showed that Zebra-Med algorithms achieved equivalent risk-stratification to contemporary fracture risk assessment tool (FRAX) scoring system.

The second five-year retrospective study, which involved 14,135 patients with non-gated, unenhanced chest CT, examined the cardiovascular predictive power of the Zebra-Med automatic coronary calcium scoring (CCS) algorithm, found that it resulted in a net 4.5% increase in categorical risk-reclassification improvement. By employing the Zebra algorithms, overstretched radiology departments can increase efficiency. Both studies were presented at the 2018 Radiological Society of North America (RSNA) annual meeting, held during November 2018 in Chicago (IL, USA).

“While there are an increasing number of AI applications in imaging aiming to mimic and automate human radiologist reading, there is larger untapped potential in these imaging studies. One can use AI to extract predictive insights unavailable to date that support high-impact population health interventions to tackle chronic diseases,” said Professor Ran Balicer, MD, the head of Clalit’s Research Institute. “We are pleased with the results of these two groundbreaking research projects and are looking forward to get them into practice.”

Related Links:
Zebra Medical Vision
Clalit Health Services

Gold Supplier
SBRT Phantom with Removable Spine
E2E SBRT Phantom with Removable Spine Model 036S-CVXX-xx
Breast Biopsy Device
Portable Suction Device
330 Multifunction Aspirator
Ultrasound System
Ultimus 9E

Print article



view channel
Image: The WHO has conditionally recommended the use of algorithms in assisting with pediatric tuberculosis diagnosis (Photo courtesy of Pexels)

New Evidence-Based Algorithms Could Improve Diagnosis of Pediatric Tuberculosis

Tuberculosis (TB) continues to be one of the most prevalent causes of death among younger populations worldwide. Research indicates that over 96% of the deadly TB cases in children under the age of 15... Read more

Surgical Techniques

view channel
Image: Robotic bronchoscopy is used to biopsy lung nodules to detect the presence of lung cancer (Photo courtesy of Pexels)

Robotic Bronchoscopy Enables Doctors to Biopsy Lung Nodules from Hard-to-Reach Areas

Bronchoscopy is a procedure commonly used to diagnose lung cancer and other lung diseases by biopsying lung nodules. Traditional bronchoscopy involves a doctor manually guiding a thin tube, known as a... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more


view channel
Image: The demand for endometrial ablation devices is increasing due to rising prevalence of gynecological disorders (Photo courtesy of Pexels)

Global Endometrial Ablation Market Driven by Rising Prevalence of Gynecological Disorders

Gynecological disorders, such as menorrhagia, PCOD, abnormal vaginal bleeding, affect millions of women globally every year and are on the rise. Abnormal Uterine Bleeding (AUB) is the most common disorder... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.