Scientific Papers

Predictive models to improve the wellbeing of heart-failure patients

Author/s: 
Aljosa Vodopija
Miha Mlakar
Mitja Lustrek
Date: 
24/Jun/2017
Event: 
Artificial Intelligence in Medicine conference, Workshop on Advanced Predictive Models in Healthcare

The paper presents an approach to providing advice on health related quality of life to patients with congestive heart failure, using predictive models built from telemonitoring data. First, by combining machine learning algorithms, feature construction, feature selection and expert knowledge, we built a set of predictive models. We then identified which of the features present in the models can be changed by the patients themselves with an appropriate intervention and modelled the association between them and all the other features using linear models.

Sexual activity in patients with heart failure

Date: 
28/May/2017
Event: 
23rd Congress of the World Association for Sexual Health, Prague, Czech Republic

Anneleen BAERT, Sofie PARDAENS, Delphine DE SMEDT, Dirk DE BACQUER, Els CLAYS

Although heart failure (HF) patients often consider sexual activity as an essential aspect of quality of life (QoL), studies concerning this topic are rather limited and are often dispersed. Factors influencing sexual activity involve physical symptoms and dysfunctions, as well as emotional and psychological concerns. Sexual counselling and exercise training are expected to have an effect. The aim of this study is to investigate this effect, using an mHealth application in HF patients.