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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Neuroimaging important for evaluating Zika-exposed infants

MRI and CT scans of infants exposed to the Zika virus in the womb revealed a range of brain abnormalities, reported authors of a recent study published in JAMA Network Open. The findings place neuroimaging as an important step in evaluating such patients.

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AI boosts accuracy of DBT, slashes radiologists’ reading times

Utilizing an AI system for digital breast tomosynthesis (DBT) can improve radiologists’ accuracy while dramatically reducing reading times, according to a new study published in Radiology: Artificial Intelligence.  

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Deep learning reads x-rays to prevent mispositioned feeding tubes

A deep learning platform can accurately distinguish critical from non-critical feeding tube placement on radiographs, according to a recent study published in the Journal of Digital Imaging.

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Imaging data backs physical activity as guard against Alzheimer’s

Increasing daily physical activity may help older adults delay their progression to Alzheimer’s disease (AD), according to research published July 16 in JAMA Neurology.  

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New AI tool may be a powerful force in cancer care

A deep learning platform created by researchers at the Dana-Farber Cancer Institute can identify cancer in radiology reports as well as clinicians, but in a fraction of the time, according to new research published July 25 in JAMA Oncology.

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4D flow MRI offers insight into COPD, emphysema

“Our multicenter study found that 4D flow MRI provided a promising way of measuring blood flow in the superior and inferior caval veins and right heart, which may provide further insight into physiologic and pathologic blood flow patterns in individuals with COPD and emphysema,” wrote researchers in a July 24 Radiology study.

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MRI reveals neurological insight into 2016 ‘auditory attack’ in Cuba

New research published July 23 in JAMA reported neurological differences in several areas of the brain, including white matter volume, among U.S. government personnel involved in a 2016 auditory attack in Cuba compared to healthy controls.

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AI identifies cancerous regions on OCT breast tissue images

A deep learning classification approach can identify cancerous regions from benign areas in optical coherence tomography (OCT) images of breast tissue, according to results of a July 17 study published in Academic Radiology.

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