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FDA approves deep learning cardiac imaging solution to assess risk of cardiovascular events

The FDA has approved an AI cardiac solution to help support clinicians in identifying patients at high risk of coronary artery disease, utilising medical imaging data to measure coronary artery calcium (CAC) as a predictor for future cardiovascular events, and potentially helping to offer more patients improved preventative care.

The solution, HealthCCSng V2.0 by Nanox, has received 510(k) clearance from the FDA, with Nanox’s CEO stating that the solution could potentially “help to bridge the divide between radiology and cardiology” and “catch patients who might otherwise fall through the cracks”.

Nanox shared that the device’s has been integrated with existing PACS systems and EHRs, and that its output is available to radiologists as “part of their standard workflow”, helping to support risk assessment and preventative healthcare for patients.

Nanox also highlighted that this marks the company’s second FDA clearance of HealthCCSng, “which now features a new “zero CAC” category, numerical CAC scoring, and CAC category configuration”.

These new features can help to enable clinicians to distinguish between patients with zero and low CAC levels, fine-tuning their cardiac risk assessments of patients, and allowing users to adjust the lower and upper boundaries for different categories of CAC scores.

In related news on AI, New York’s Mount Sinai Health System has announced a new research collaboration with IBM Research, Harvard, Johns Hopkins, Columbia, Carnegie Mellon, and Deliberate AI, using AI and behavioural data to predict outcomes such as treatment discontinuation, hospitalisations, and ED visits for young people seeking mental health evaluation and treatment.

In Canada, with demand predicted to increase by 10 percent by 2033, public emergency medical service Urgences-santé Quebec has partnered with Canadian-based SME Airudi to develop the MODUS platform, which harnesses AI to offer “real-time prediction” of pre-hospital service demands.

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