Mining association rules between stroke risk factors based on the Apriori algorithm.

Background: Stroke is a frequently-occurring disease and is a severe threat to human health.

Objective: We aimed to explore the associations between stroke risk factors.

Methods: Subjects who were aged 40 or above were requested to do surveys with a unified questionnaire as well as laboratory examinations.

Paroxysmal atrial fibrillation recognition based on multi-scale Rényi entropy of ECG.

Background: Atrial fibrillation (AF) is a common type of arrhythmia disease, which has a high morbidity and can lead to some serious complications. The ability to detect and in turn prevent AF is extremely significant to the patient and clinician.

Objective: Using ECG to detect AF and develop a robust and effective algorithm is the primary objective of this study.