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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FDA greelights AI algorithms that detect heart murmurs, AFib via stethoscope

The FDA has cleared a series of AI algorithms designed by California tech company Eko to facilitate the detection of atrial fibrillation and heart murmurs.

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What MRI and 100 years of horror movies can teach us about our brains

Finnish researchers had volunteers watch two of the century's scariest horror films inside an MRI machine while recording their brain activity, sharing their findings this month in NeuroImage.

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AppliedVR, UCSF work to improve healthcare for vulnerable patient populations

AppliedVR, a Los Angeles-based virtual reality (VR) company, has announced a new research project focused on improving care for Medicaid patients and other vulnerable populations. 

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Coronavirus patient in US treated with stethoscope-wielding robot

The first person diagnosed with the deadly Wuhan coronavirus in the United States is receiving care from a small team of healthcare providers and an advanced robot.

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Sex, money and food: fMRI reveals how the brain processes rewards

These three items activate similar brain locations, according to the study published this month in Brain and Imaging Behavior, but do so in very different ways.

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AI reads images in milliseconds—bringing low-cost malaria detection to resource-strapped areas

The deep learning model can identify parasites that cause the disease in blood sample images as accurately as human experts, but in a fraction of the time, researchers wrote in the Journal of Digital Imaging.

 

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Competing realities: AR on way to surpassing VR in healthcare space

Both virtual reality (VR) and augmented reality (AR) are on their way to playing key roles in the delivery of healthcare—but AR may have the brighter future.

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Experts urge radiology to be more cognizant of image resolution’s impact on AI

Two researchers found that using certain pixel dimensions helped tailor algorithms to detect specific abnormalities, and pushed radiology to keep this in mind when using such approaches.