AI Program Could Aid Decision-Making in Medical Imaging
|
By HospiMedica 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).
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
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
Latest AI News
- Privacy-Preserving AI Protects Sensitive Information in ECG Data
- New AI ECG Tool Detects Early Heart Disease
- AI Platform Supports Noninvasive Remote Hemodynamic Monitoring in Heart Failure
- AI Tool Predicts Unplanned Care and Symptom Burden in Cancer Survivors
- Automated Phone Speech Test Identifies Alzheimer’s Pathology for Prescreening
- FDA-Cleared AI System Detects Sepsis Earlier and Reduces Mortality
- Facial Image Analysis Tracks Biological Aging, Predicts Cancer Outcomes
- AI Model Uses Eye Imaging to Identify Risk of Major Systemic Diseases
Channels
Artificial Intelligence
view channel
Privacy-Preserving AI Protects Sensitive Information in ECG Data
Artificial intelligence applied to electrocardiography can extract more than cardiac rhythm. Algorithms can infer age, sex, race, and even identity from electrocardiogram (ECG) signals, creating privacy... Read more
New AI ECG Tool Detects Early Heart Disease
Heart disease remains a leading cause of premature death, claiming almost 18 million lives each year. Early detection is crucial because timely intervention can change prognosis and conserve resources.... Read moreCritical Care
view channel
Eye Test May Predict Return of Consciousness After Severe Brain Injury
Severe brain injury often leads to acute disorders of consciousness, leaving clinicians uncertain about prognosis. Early, reliable prediction of recovery is central to guiding goals of care, sedation strategies,... Read more
AI System Enables Real-Time Sepsis Quality Assessment and Improves Adherence
Sepsis is a time-sensitive emergency requiring rapid, coordinated care, yet clinicians often lack timely performance feedback. Complex chart reviews tied to national quality measures can take months, delaying... Read moreSurgical Techniques
view channel
Living Valve Surgery Delivers Durable Outcomes for Aortic Valve Disease
Aortic valve disease can lead to heart failure, impaired quality of life, and early mortality if untreated, yet standard replacement options often require trade-offs among durability, anticoagulation,... Read more
Minimally Invasive Embolization Procedure Reduces Knee Osteoarthritis Pain
Chronic knee pain from osteoarthritis, a degenerative joint disease, limits mobility and drives high use of analgesics and surgery. Many patients fail conservative therapy yet are not ready for arthroplasty,... Read morePatient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read moreHealth IT
view channel
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read moreAI Framework Helps Clinicians Create Trustworthy Risk Prediction Tools
Artificial intelligence (AI) is increasingly used to estimate risks for conditions such as sepsis, heart disease, and cancer, yet many models remain difficult for clinicians to interpret or trust.... Read morePoint of Care
view channel
Handheld AI Device for Point-of-Care Skin Lesion Assessment Receives CE Mark
DermaSensor (Miami, FL, USA) has received a Class IIb CE Mark for its handheld DermaSensor device, marking the start of the company’s global expansion strategy. The certification demonstrates conformity... Read more
Portable Immunoassay System Advances Toward Point-of-Care Biomarker Testing
Proxim Diagnostics Corp. (Santa Clara, CA, USA) has announced that its Profile System, a handheld point-of-care immunoassay platform, has completed development. The milestone includes completion... Read more
Portable MRI System Accelerates Emergency Brain Imaging and Triage
Emergency departments frequently face delays accessing conventional magnetic resonance imaging (MRI) for patients with suspected neurological emergencies. Such waits can slow triage, prolong boarding,... Read more







