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. 

EnvoyAI, TeraRecon, Insignia partner to bring AI to UK customers

EnvoyAI today announced a new integration with Insignia Medical Systems’ InSight PACS to provide artificial intelligence (AI)-enhanced imaging workflows to customers.

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ACR’s Allen on partnering with MICCAI, the future of AI

Bibb Allen Jr., MD, chief medical officer with the American College of Radiology (ACR)’s Data Science Institute (DSI) talked with HealthImaging about focusing Medical Image Computing and Computer Assistance Intervention's (MICCAI) artificial intelligence (AI) challenges on radiologists' clinical needs.

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Cost-effective AI model produces 3D cell images

A new artificial intelligence (AI) tool lets scientists visualize a three-dimensional (3D) model of living human cells, even when the entire cell is not visible, according to a recent NPR story.

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Machine learning tool IDs emerging bacteria before causing outbreak

Using genomic sequencing to identify mutations in emerging strains of bacteria responsible for or at-risk of causing an outbreak is time consuming and labor-intensive. However, researchers have recently developed a new machine learning tool that can speed up the process.

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'Glove' prototype captures MRI of joints in action

MRI, for all it can do, has many design limitations—but an NYU School of Medicine team recently created an MRI device that users can slip on like a glove to produce high quality images of moving joints.

Machine learning IDs dangerous bacterial strains

A team from the Wellcome Sanger Institute in the United Kingdom, the University of Otago in New Zealand and the Helmholtz Institute for RNA-based Infection Research in Germany has developed a machine learning tool capable of detecting strains of salmonella before they cause bloodstream infections. Findings were published May 8 in PLOS Genetics.

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Machine learning beats traditional method in diagnosing autism spectrum disorders

Researchers have found a new method utilizing established data sets and a machine learning algorithm that can outperform traditional methods of diagnosing autism spectrum disorders (ASD) in young children, which could improve accuracy in early diagnosis.

Ultrasound helmet may break down health barriers

A group at Vanderbilt University in Nashville is developing a helmet that would use ultrasound brain technology to produce real-time images with novel implications for surgery guidance and robotics, according to a university press release.