Rapid AI adoption in the field of cardiology

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Medical device companies have had to rapidly adopt emerging technologies such as artificial intelligence (AI) to accommodate the lack of in-person visitations during the Covid-19 pandemic. GlobalData forecasts that medical device companies’ spending on AI is set to witness a compound annual growth rate of 20.6% between 2019 and 2024, and this trend is expected to continue in the future.

Recently, the FDA published a list of artificial AI-enabled medical devices that were approved by the FDA in 2022. Approximately 57% of these devices fall under cardiology. One area of cardiology where researchers are trying to incorporate AI is in predicting heart attacks before they happen.

According to the World Health Organization, approximately 17.9 million people die of cardiovascular diseases every year, making cardiovascular diseases the world’s leading cause of death. In the US alone, a heart attack occurs every 40 seconds. By using AI, physicians are now able to analyse copious amounts of patient information to determine who is at risk of a heart attack and when it could potentially happen.

Cedars-Sinai recently developed an AI-enabled tool that analyses medical images and identifies the patterns and signs of heart disease. More specifically, it examines patterns of plaque accumulation in arteries. In doing so, it enables physicians to better assess a patient’s likelihood of experiencing a heart attack in the future.

GlobalData forecasts that healthcare providers will be spending the most on AI platforms in 2024, at approximately $2.9bn. Questions remain about whether AI will be replacing some healthcare professionals’ roles during patients’ treatment journeys, such as those currently filed by doctors. However, AI is not capable of cultivating a trust bond, as occurs between doctors and patients. While AI can certainly help physicians to better diagnose patients, AI could never replicate the human aspect of healthcare.

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• Source: https://www.medicaldevice-network.com/comment/ai-adoption-cardiology/