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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AI model evaluates ECG data as well as cardiologists

The team's convolutional neural network was trained on data that is readily available at most facilities. 

Medtronic gains FDA approval for AI models focused on cardiac monitoring

The advanced algorithms address two areas known for causing false ICM alerts: atrial fibrillation and asystole.

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Want a more accurate AI model for predicting CVD? Feed it social data

Researchers stressed that clinicians have an opportunity to improve their machine learning models by providing data on specific social and environmental factors. 

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AI model predicts diabetes risk using MRI results

The algorithm measures the amount of fat surrounding a person's heart, using that information to create an accurate diabetes risk assessment. 

Tai chi could help ease depression, anxiety among stroke survivors

An eight-week tai chi course provided key benefits for older stroke survivors, researchers reported. 

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Combining AI with cardiac imaging helps predict heart attacks, cardiovascular deaths

The findings were presented virtually during the Society of Nuclear Medicine and Molecular Imaging's 2021 Annual Meeting.

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New AI model uses readily available healthcare data to predict type 2 diabetes

The team’s algorithm was trained, validated and tested with data from a total of more than 2.1 million patients.

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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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