3 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ME2022
How much of the past matters? Using dynamic survival models for the monitoring of potassium in heart failure patients using electronic health records
Caterina Gregorio, Giulia Barbati, Arjuna Scagnetto +2
Statistical methods to study the association between a longitudinal biomarker and the risk of death are very relevant for the long-term care of subjects affected by chronic illness…
eess.SP2022★ 3 cited
Deep artificial neural network for prediction of atrial fibrillation through the analysis of 12-leads standard ECG
A. Scagnetto, G. Barbati, I. Gandin +7
Atrial Fibrillation (AF) is a heart's arrhythmia which, despite being often asymptomatic, represents an important risk factor for stroke, therefore being able to predict AF at the…