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 Program Could Aid Decision-Making in Medical Imaging

By MedImaging International staff writers
Posted on 24 Sep 2018
Image: The Explainable Artificial Intelligence (XAI) program can help with decision-making in various medical fields (Photo courtesy of Raytheon BBN Technologies).
Image: The Explainable Artificial Intelligence (XAI) program can help with decision-making in various medical fields (Photo courtesy of Raytheon BBN Technologies).
Researchers are developing a first of its kind neural network that explains itself and could help with decision-making in the medical field, among others. Raytheon BBN Technologies (Cambridge, MA, USA) is developing the neural network under the Defense Research Project Agency's (DARPA) Explainable Artificial Intelligence program (XAI). The aim of the XAI program is to create a suite of machine learning techniques, which produce more explainable models while maintaining a high level of performance. It also aims to help human users understand, appropriately trust and effectively manage the emerging generation of artificially intelligent partners.

The Explainable Question Answering System (EQUAS) by Raytheon BBN will allow Artificial Intelligence (AI) programs to 'show their work,' increasing the human user's confidence in the machine's suggestions. EQUAS will show users which data mattered most in the AI decision-making process. Using a graphical interface, users can explore the system's recommendations and see why it chose one answer over another. Although the technology is still in its early phases of development, it has the potential to be used for a wide-range of applications. As the system is enhanced, EQUAS will be able to monitor itself and share factors that limit its ability to make reliable recommendations. This self-monitoring capability will help developers refine AI systems, allowing them to inject additional data or change how data is processed.

"A fully developed system like EQUAS could help with decision-making not only in DoD operations, but in a range of other applications like campus security, industrial operations and the medical field," said Bill Ferguson, lead scientist and EQUAS principal investigator at Raytheon BBN. "Say a doctor has an x-ray image of a lung and her AI system says that its cancer. She asks why and the system highlights what it thinks are suspicious shadows, which she had previously disregarded as artifacts of the X-ray process. Now the doctor can make the call – to diagnose, investigate further, or, if she still thinks the system is in error, to let it go."

Related Links:
Raytheon BBN Technologies

Ultrasonic Pocket Doppler
SD1
Portable Color Doppler Ultrasound Scanner
DCU10
Digital Intelligent Ferromagnetic Detector
Digital Ferromagnetic Detector
Multi-Use Ultrasound Table
Clinton

Channels

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.