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. 

Injectable ultrasound chip wirelessly monitors, treats preclinical patients

Biomedical and electrical engineers have invented a probe so small it must be inserted hypodermically yet can monitor vital signs and even stimulate tissue for therapeutic purposes.

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AI startup Whiterabbit exits stealth mode to announce FDA-cleared breast density software, new CEO

The Santa Clara, California-based company has raised more than $49 million in funding and inked partnerships with providers including RadNet and the Mallinckrodt Institute of Radiology. 

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More than 60% of radiologists believe ethical, legal issues will hinder widespread AI adoption

The findings are the second installment of an international survey analyzing attitudes toward artificial intelligence in imaging.

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Combining imaging data, genomic info may increase radiologists’ confidence diagnosing cancer

UCLA radiological experts unveiled their neural network framework in the Journal of Medical Imaging.

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AI model helps clinicians predict post-TAVR infective endocarditis

To build and validate their advanced AI model, researchers explored data from nearly 78,000 TAVR hospitalizations.

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New 3D MRI development captures real-time brain movement in ‘stunning’ detail

Radiologists and other clinicians may use 3D-amplified MRI as a complement to guide their treatment decision-making, according to recently published research papers.

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Artificial intelligence may not upend radiology until 2030s, noted Google AI expert predicts

Leaders in the space shared their predictions for imaging AI during a panel hosted by the Stanford Institute for Human-Centered Artificial Intelligence. 

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Advanced MRI uncovers neurological insights in patients with Down syndrome

The results support using magnetic resonance imaging biomarkers to study drug-based approaches for enhancing cognitive function.