Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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UCLA researchers use MRI, AI predict value of therapy for OCD patient

Through functional MRI (fMRI) and machine learning technology, UCLA researchers have developed a way to predict whether individuals with obsessive compulsive disorder (OCD) will benefit from cognitive behavioral therapy (CBT), according to a recent UCLA release.  

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FDA grants 1st permission for AI stroke-detection imaging software

According to a Feb. 13 press release, the FDA announced clearance for the marketing of the Viz.AI Contact application, a clinical decision support software created to analyze CT results and notify providers of a potential stroke.

Has imaging spied a connection between alcohol, anger?

Why does it seem like when alcohol gets involved, people often exhibit more aggressive behavior thanks to “liquid courage”? According to a group of international researchers, it’s because changes occur in the prefrontal cortex—the area of the brain charged with tempering a person’s aggression—after two drinks. 

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More hospitals than imaging centers are adopting AI, new report says

According to a December 2017 research survey conducted by the healthcare market research firm Reaction Data, most hospitals and imaging centers will be using machine learning or artificial intelligence (AI) technology by 2020.

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AI and machine learning in radiology: 4 things to know

As industry experts continue to explore artificial intelligence (AI) applications in radiology, the question remains of whether AI applications can and will add value, including in new knowledge and information to provide patients with better outcomes at lower costs.

PSMA PET, CT detects recurrent prostate cancer early, guides radiotherapy

Nuclear imaging may better locate recurrent prostate cancer after prostatectomy and aid in earlier detection after recurrence all while simultaneously providing the sensitive imaging needed to guide salvage radiotherapy in patients, according to a study in the February issue of The Journal of Nuclear Medicine.

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How accurate is machine learning in speech recognition? Researchers take a look

Artificial intelligence and machine learning are all the rage—and for good reason. But researchers claim the brain doesn’t actually use the regions identified by machine learning to perform a task. Rather, these algorithms reflect the mental associations related to the task.

UAE envisions successful future with AI

The United Arab Emirates will bring the first radiology artificial intelligence (AI) algorithm in the state to its medical fitness centers as part of the Dubai Health Authority’s (DHA) Dubai Health Strategy 2021, the Gulf News reports.

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GE HealthCare launches new cardiac CT scanner with advanced AI capabilities

GE HealthCare designed the new-look Revolution Vibe CT scanner to help hospitals and health systems embrace CCTA and improve overall efficiency.

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Bracco updates HeartSee coronary flow capacity software with new diagnostic features

Clinicians have been using HeartSee to diagnose and treat coronary artery disease since the technology first debuted back in 2018. These latest updates, set to roll out to existing users, are designed to improve diagnostic performance and user access.

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Key trends in diagnostic heart testing: CT on the rise as some traditional techniques fall out of favor

The cardiac technologies clinicians use for CVD evaluations have changed significantly in recent years, according to a new analysis of CMS data. While some modalities are on the rise, others are being utilized much less than ever before.