dismiss

Clean Sweep Live Auction on Thur. March 28th. Click to view the full inventory

DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Mobile Imaging
SEARCH
Current Location:
>
> This Story


Log in or Register to rate this News Story
Forward Printable StoryPrint Comment
Advertisement

 

advertisement

 

Health IT Homepage

Healthcare’s ‘valueless data’ problem Information is collected and organized, time to put it to work

Study: 'Convenient' telehealth visits lack coordinated relaying of information Could lead to fragmentation in healthcare, say study authors

Augmented reality bridging the physical and digital gap in healthcare Understanding how AR is allowing for better medical outcomes

Fujifilm and Epsilon Imaging partner to enhance echocardiographic reading Integrating EchoInsight with Fujifilm's Synapse Cardiology PACS

Carestream sells health IT business to Philips Citing 'complementary geographic footprint' Philips acquires leading enterprise imaging platform

Data sharing for imaging trials low, says ESR research committee at ECR Interest is high but concerns remain

Varex Imaging expands service offering to Europe, releases new tube and detector line at ECR Provide technical and logistical support for installations

Canon showcases CT image reconstruction tech and software upgrade at ECR Removing noise while preserving signals

Analytics was a buzzword at HIMSS, but only half of hospitals are taking advantage Physician buy-in is crucial to implementing change

Q&A with Dr. David Asch, executive director of the Penn Medicine Center for Health Care Innovation What can be done to make EHRs a more seamless part of hospital workflow?

Artificial Intelligence applied successfully to orthopedic X-ray images in study

by John W. Mitchell , Senior Correspondent
A team of Swedish researchers said they have, for the first time, demonstrated the feasibility of using deep AI learning for orthopedic trauma radiographs (X-rays). Their study was just published in the Journal of Acta Orthopaedic.

The team created a database of 256,000 wrist, hand and ankle radiographs, composed of four classes of fractures. These included fracture, laterality, body part, and exam view. They then selected five open, available deep learning networks adapted for the images to create a gold standard for fractures. Ankles were the most common body part (38 percent), with right extremity (52 percent) slightly more common than left. The anteroposterior was the most common view.

Story Continues Below Advertisement

RaySafe helps you avoid unnecessary radiation

RaySafe solutions are designed to minimize the need for user interaction, bringing unprecedented simplicity & usability to the X-ray room. We're committed to establishing a radiation safety culture wherever technicians & medical staff encounter radiation.



They next compared the network's performance with the findings of two orthopedic surgeons who reviewed the images at the same resolution as the AI network. The accuracy stats in the study indicate that the AI and physicians agreed that a fracture was present in at least 80 percent of cases.

"Our results could be used as a second screening, thereby increasing patient safety and helping junior physicians that lack access to a radiologist, " Dr. Max Gordon, Department of Clinical Sciences, Karolinska Institute, Danderyd Hospital in Stockholm and a member of the research team, told HCB News. "The real benefit will come a few years down the line when we can diagnose a wide range of diseases and ideally also link this knowledge to treatment options."

The study concluded that the findings support further development of the AI application in orthopedics. It takes years of training for orthopedic physicians to train to read such films, yet "inter-observer reliability" can be a big variable in effectiveness and outcomes.

There were certain circumstances in which orthopedic physicians still excel in reading images. These included: the risk of dislocation, classifications, measurements and combining multiple exam views. But, the study concluded, these challenges have technical solutions.

"Even once we have the perfect AI, it is not certain that it will be what doctors and patients expect," Gordon cautioned. "Just as the first smartphones were fun but rather underwhelming, this technology in its first iterations will not solve all our problems."

However, the major intent of the study - to determine if deep AI can be trained to identify fractures - was successful. Given that X-ray still remains the most common and cost-effective orthopedic diagnostic tool worldwide, the research team is encouraged by the results.

"It is a safe bet that that AI will have a large impact, as it has worked well in similar settings," noted Gordon. "There have been interesting developments in areas such as dermatology and breast cancer, where images are an important source of diagnosis."

Health IT Homepage


You Must Be Logged In To Post A Comment

Advertise
Increase Your
Brand Awareness
Auctions + Private Sales
Get The
Best Price
Buy Equipment/Parts
Find The
Lowest Price
Daily News
Read The
Latest News
Directory
Browse All
DOTmed Users
Ethics on DOTmed
View Our
Ethics Program
Gold Parts Vendor Program
Receive PH
Requests
Gold Service Dealer Program
Receive RFP/PS
Requests
Healthcare Providers
See all
HCP Tools
Jobs/Training
Find/Fill
A Job
Parts Hunter +EasyPay
Get Parts
Quotes
Recently Certified
View Recently
Certified Users
Recently Rated
View Recently
Certified Users
Rental Central
Rent Equipment
For Less
Sell Equipment/Parts
Get The
Most Money
Service Technicians Forum
Find Help
And Advice
Simple RFP
Get Equipment
Quotes
Virtual Trade Show
Find Service
For Equipment
Access and use of this site is subject to the terms and conditions of our LEGAL NOTICE & PRIVACY NOTICE
Property of and Proprietary to DOTmed.com, Inc. Copyright ©2001-2019 DOTmed.com, Inc.
ALL RIGHTS RESERVED