En Es
Categories

Industry News

New AI System Prioritizes Chest X-Rays Containing Critical Findings

By Medimaging International staff writers
07 Feb 2019

Image: Examples of correctly and incorrectly prioritized radiographs. (a) Radiograph was reported as showing large right pleural effusion (arrow). This was correctly prioritized as urgent. (b) Radiograph reported as showing “lucency at the left apex suspicious for pneumothorax.” This was prioritized as normal. On review by three independent radiologists, the radiograph was unanimously considered to be normal. (c) Radiograph reported as showing consolidation projected behind heart (arrow). The finding was missed by the artificial intelligence system, and the study was incorrectly prioritized as normal (Photo courtesy of RSNA).A team of UK researchers has trained an artificial intelligence (AI) system to interpret and prioritize abnormal chest X-rays with critical findings, thereby creating the potential for reducing the backlog of exams and bringing urgently needed care to patients more quickly.

Globally, chest X-rays account for 40% of all diagnostic imaging and the number of exams can create significant backlogs at health care facilities. Deep learning (DL), a type of AI that is capable of being trained to recognize subtle patterns in medical images, is being seen as an automated means to reduce this backlog and identify exams that warrant immediate attention, particularly in publicly funded health care systems.

In their study, the researchers used 470,388 adult chest X-rays to develop an AI system that could identify key findings. The radiologic reports were pre-processed using Natural Language Processing (NLP), an important algorithm of the AI system that extracts labels from written text. For each X-ray, the researchers' in-house system required a list of labels indicating which specific abnormalities were visible on the image.

The NLP analyzed the radiologic report to prioritize each image as critical, urgent, non-urgent or normal. An AI system for computer vision was then trained using labeled X-ray images to predict the clinical priority from appearances only. The researchers tested the system's performance for prioritization in a simulation using an independent set of 15,887 images. The AI system distinguished abnormal from normal chest X-rays with high accuracy. Simulations showed that critical findings received an expert radiologist opinion in 2.7 days, on average, with the AI approach—significantly sooner than the 11.2-day average for actual practice.

"The initial results reported here are exciting as they demonstrate that an AI system can be successfully trained using a very large database of routinely acquired radiologic data," said study co-author Giovanni Montana, Ph.D., formerly of King's College London in London and currently at the University of Warwick in Coventry, England. "With further clinical validation, this technology is expected to reduce a radiologist's workload by a significant amount by detecting all the normal exams so more time can be spent on those requiring more attention."



E-mail Print
FaceBook Twitter Google+ Linked in

Additional news

13 Aug 2019
Siemens Healthineers' Acquires Corindus to Enhance Robotic-Assisted Interventions
Siemens Healthineers AG has entered into a merger agreement with Corindus Vascular Robotics, Inc. to acquire the company, which offers a robotic treatment platform for the major vascular therapeutic markets, including coronary, peripheral vascular and neurovascular interventions.
Read More
05 Aug 2019
Siemens Healthineers Receives Recognition AI Applications in Radiology
Based on its recent analysis of the global precision imaging market, Frost & Sullivan, a growth strategy consulting and research firm, has recognized Siemens Healthineers with the 2019 Global Visionary Innovation Leadership Award for leading the effort to establish imaging as an active contributor to precision medicine.
Read More
29 Jul 2019
Ampronix Offers One-Stop Solution for Cath Lab Display Monitors
A catheterization laboratory, commonly referred to as cath lab, is a vital piece of diagnostic equipment for hospitals and healthcare facilities.
Read More
17 Jul 2019
Machine Learning Can Predict Heart Disease Better Than Other Risk Models
A study conducted by researchers from the Yale School of Medicine has demonstrated that machine learning (ML), a type of artificial intelligence, performs better than conventional risk models at predicting heart attacks and other cardiac events when used along with a common heart scan.
Read More
17 Jul 2019
Global Portable X-Ray Devices Market to Reach USD 6.87 Billion by 2022
The global portable X-ray devices market grew at a compound annual growth rate (CAGR) of 8.8% from 2014 to 2018 to reach nearly USD 4.70 billion in 2018 and is projected to grow at a CAGR of 10% from 2018 to 2022 to reach almost USD 6.87 billion by 2022.
Read More
17 Jul 2019
Global Portable Ultrasound Devices Market to Reach USD 6.85 Billion by 2022
The global portable ultrasound devices market grew at a compound annual growth rate (CAGR) of 21% from 2014 to 2018 to reach nearly USD 3.03 billion in 2018 and is projected to grow at a CAGR of 22.6% from 2018 to 2022 to reach almost USD 6.85 billion by 2022.
Read More
17 Jul 2019
Agilent Technologies Expands Portfolio with Acquisition of BioTek Instruments
Agilent Technologies Inc., a global leader in the life sciences, diagnostics and applied chemical markets, has signed a definitive agreement to acquire privately-owned BioTek Instruments, which designs, manufactures, and distributes innovative life science instrumentation.
Read More
06 Jul 2019
ACR Expands Pilot Program Focused on AI and Radiology
Radiology professionals from seven renowned health care institutions will use the ACR AI-LAB to demonstrate the process of creating investigational artificial intelligence (AI) models from image data without the use of a programming language.
Read More
06 Jul 2019
Konica Minolta Offers AI-Based Cardiac Ultrasound Analysis
Konica Minolta Healthcare Americas Inc, a provider of medical diagnostic imaging and healthcare information technology, has announced a partnership with DiA Imaging Analysis, a provider of artificial intelligence (AI) powered ultrasound analysis solutions.
Read More
Copyright © 2000-2019 TradeMed.com. All rights reserved. | Terms And Conditions