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. 

Fitbit’s latest AFib algorithm receives FDA clearance, will be available ‘soon’

The new algorithm was designed to evaluate a user's heart rhythm while they are still or even sleeping. 

Smartwatch app accurately detects atrial fibrillation in large Chinese study

A Chinese study of 2.8 million participants found that 94% of users flagged for AFib indeed have the heart rhythm disorder.

Los Angeles, California

Australian tech company opens new US office, eyes FDA approval for AI CAD solution

The company's flagship offering uses AI to evaluate 3D images of a patient's heart for signs of atherosclerotic plaque.

AI model able to ID early signs of type 2 diabetes on imaging results

The authors hope their findings could lead to earlier diagnoses and improvements in patient care. 

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AI distinguishes between a heart attack and takotsubo syndrome more accurately than cardiologists

The advanced AI model outperformed a team of cardiologists, delivering a better AUC and overall accuracy. 

chest pain lung pulmonary embolism

Image quality is not an issue for AI model that detects pulmonary embolisms on CT

CTPA is the standard of care for diagnosing PE, but suboptimal scans make it difficult to reach a diagnosis. A new Clinical Imaging study tests the effectiveness of AI when image quality is lacking.

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AI-powered ECG analysis could boost care for patients with hypertrophic cardiomyopathy

Advanced algorithms can pick up on key details in a 12-lead ECG that human readers are unable to see. 

AFib, AI and heart-healthy diets: European Society of Cardiology previews EHRA 2022

The European Heart Rhythm Association's annual conference is headed to Denmark. 

Around the web

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.