Editorial on an autoencoder algorithm for the prediction of stroke patients with left ventricular thrombus (LVT)

In this research paper, Hargreaves et al., used an autoencoder model to classify the patients with left ventricular thrombus for high or low risk of stroke. The authors examined various factors to elucidate which ones had pivotal roles in predicting the risk factors for stroke. They concluded that individuals with a previous history of stroke, those who experienced transient ischemic strokes, and those who took anticoagulation medicine for longer durations were more likely to be categorized as being at a high risk of stroke.
Source: Journal of the Neurological Sciences - Category: Neurology Authors: Source Type: research