Clinical researchers at Mayo Clinic, working with AliveCor, the company that essentially introduced mobile electrocardiography (ECG) to the mass market, have published a study abstract demonstrating that artificial intelligence can be used to spot patients with congenital Long QT Syndrome (LQTS). The readings come from lead 1 of a 12-lead clinical grade ECG, which means that AliveCor’s single lead ECGs, such as the Kardia Band for the Apple Watch, should be able to do the same trick.
Some details according to AliveCor:
As many as 50% of patients with genetically confirmed LQTS have a normal QT interval on the standard ECG, so identifying these patients who are at increased risk of arrhythmias and sudden cardiac death is crucial for correct diagnosis and treatment. This is especially critical when patients are exposed to medications with known QT prolonging potential. The deep neural network employed in the study generated an area under the curve of 0.83, with a specificity of 81%, sensitivity of 73%, and an overall accuracy of 79%.