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
ARAB HEALTH - INFORMA

Download Mobile App




Artificial Intelligence Accurately Detects Fractures on X-Rays

By HospiMedica International staff writers
Posted on 13 Jan 2022
Print article
Image: Examples of fractures detected using the AI BoneView algorithm (Photo courtesy of BUSM)
Image: Examples of fractures detected using the AI BoneView algorithm (Photo courtesy of BUSM)
A new study reveals that artificial intelligence (AI) assistance improves the sensitivity and specificity of radiology readers searching for skeletal fractures.

Researchers at Boston University School of Medicine (BUSM; MA, USA), Stony Brook University (SBU; NY, USA), and other institutions conducted a study of the Gleamer (Paris, France) AI BoneView algorithm, which can detect fractures of the limbs, pelvis, torso, lumbar spine, and rib cage. Six types of readers (radiologists, orthopedic surgeons, emergency physicians, physician assistants, rheumatologists, and family physicians) examined set 480 data sets, both with and without AI BoneView.

The results revealed that using AI assistance helped reduce missed fractures by 29% and increased readers' sensitivity by 16% for a single fracture, and by 30% for exams with more than one fracture, while improving specificity by 5%. The improvement in sensitivity was significant in all locations, but especially in the shoulder, clavicle, and thoracolumbar spine. AI assistance also shortened X-ray reading time by an average of 6.3 seconds per patient. The study was published on December 21, 2021, in Radiology.

“Our AI algorithm can quickly and automatically detect x-rays that are positive for fractures and flag those studies in the system so that radiologists can prioritize reading x-rays with positive fractures,” said corresponding author Professor Ali Guermazi, MD, PhD, of BUSM. “The system also highlights regions of interest with bounding boxes around areas where fractures are suspected. This can potentially contribute to less waiting time at the hospital or clinic before patients can get a positive diagnosis of fracture.”

Missed fractures on radiographs are one of the most common causes of diagnostic discrepancies between initial interpretations by non-radiologists or residents and the final read by board-certified radiologists, leading to preventable harm or delay in care to the patient. In addition, inconsistencies in radiographic diagnosis of fractures are more common during the evening and overnight hours, likely related to non-expert reading and fatigue. In patients with multiple traumas, the proportion of missed injuries, including fractures, can be high on the forearm and hands (6.6%) and feet (6.5%).

Related Links:
Boston University School of Medicine
Stony Brook University
Gleamer


Gold Member
12-Channel ECG
CM1200B
Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
New
Ultrasound Table
General 3-Section Top EA Ultrasound Table
New
MRI System
Ingenia Prodiva 1.5T CS

Print article

Channels

Critical Care

view channel
Image: An in-situ curing strategy to develop a stretchable, semi-transparent, and durable GPE-TENG (Photo courtesy of Pandey et al. (2024), Chemical Engineering Journal; DOI: 10.1016/j.cej.2024.156650)

Gel-Based Stretchable Triboelectric Nanogenerators to Revolutionize Wearable Technology

Wearable technology, ranging from fitness trackers and smartwatches to medical sensors worn on the body, is revolutionizing our interaction with technology. As these devices gain in popularity, triboelectric... Read more

Surgical Techniques

view channel
Image: The first-ever surgery performed utilizing the MARS platform and Intuitive Da Vinci SP single-port robot (Photo courtesy of Levita Magnetics)

Revolutionary Robotic Surgery Combines Dual-System Technologies for Groundbreaking Prostate Procedure

In a pioneering advancement for robotic-assisted surgery, surgeons at UT Southwestern Medical Center (Dallas, TX, USA) have successfully performed the first-ever surgery utilizing two distinct systems... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... 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 acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.