Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Adelaide, Austral ia, by NewsRx journalists, research stated, “Biological age can be predicted usi ng artificial intelligence (AI) trained on electrocardiograms (ECGs), which is p rognostic for mortality and cardiovascular events. We developed an AI model to p redict age from ECG and compared baseline characteristics to identify determinan ts of advanced biological age.” The news correspondents obtained a quote from the research from Royal Adelaide H ospital, “An AI model was trained on ECGs from cardiology inpatients aged 20-90 years. AI analysis used a convolutional neural network with data divided in an 8 0:20 ratio (development:internal validation), with external validation undertake n using data from the UK Biobank. Performance and subgroup comparison measures i ncluded correlation, difference and mean absolute difference. 63,246 patients wi th 353,704 total ECGs were included. In internal validation, the correlation coe fficient was 0.72, with a mean absolute difference between chronological and AI- predicted age of 9.1 years. The same model performed similarly in external valid ation. In patients aged 20-29, AI-ECG biological age was older than chronologica l age by a mean 14.3±0.2 yrs. In patients aged 80-89 years, biological age was y ounger by a mean 10.5±0.1 yrs. Women were biologically younger than men by a mea n of 10.7 months (P=0.023) and patients with a single ECG were biologically 1.0 years younger than those with multiple ECGs (P <0.0001). Th ere are significant between-group differences in AI-ECG biological age for patie nt subgroups. Biological age was greater than chronological age in young, hospit alized patient, and less than chronological age in the older hospitalized patien t.”
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