Association of daily physical activity with pulmonary artery pressure in HFpEF and HFmrEF NYHA class III patients: a pilot trial-feasibility and first results.

Introduction: Supervised physical exercise has been shown to benefit patients with heart failure with preserved/mildly reduced ejection fraction (HFpEF/HfmrEF) by improving symptoms and diastolic function. This study aimed to investigate the correlation between unsupervised daily physical activity and changes in daily pulmonary artery pressure (PAP) in patients with stable NYHA class III heart failure (HF) and left ventricular ejection fraction (LVEF) of 45% or higher.

Methods: Daily physical activity was monitored over a 3-month period using a Holter-ECG with an accelerometer that calculated an activity-associated, heart rate-derived metabolic equivalent of task (MET) score.

A Hybrid AI-Based Method for ICD Classification of Medical Documents.

Automatic document classification is a common problem that has successfully been addressed with machine learning methods. However, these methods require extensive training data, which is not always readily available. Additionally, in privacy-sensitive settings, transfer and reuse of trained machine learning models is not an option because sensitive information could potentially be reconstructed from the model.

An empirical evaluation of a novel domain-specific language - modelling vehicle routing problems with Athos.

Unlabelled: Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL models into executable software code. Often, DSLs are even claimed to reduce development complexity to a level that allows them to be successfully applied by domain-experts with limited programming knowledge.

The Disruption of Trust in the Digital Transformation Leading to Health 4.0.

The specification and application of policies and guidelines for public health, medical education and training, and screening programmes for preventative medicine are all predicated on trust relationships between medical authorities, health practitioners and patients. These relationships are in turn predicated on a verbal contract that is over two thousand years old. The impact of information and communication technology (ICT), underpinning Health 4.

Identifying Heart Failure in ECG Data With Artificial Intelligence-A Meta-Analysis.

Electrocardiography (ECG) is a quick and easily accessible method for diagnosis and screening of cardiovascular diseases including heart failure (HF). Artificial intelligence (AI) can be used for semi-automated ECG analysis. The aim of this evaluation was to provide an overview of AI use in HF detection from ECG signals and to perform a meta-analysis of available studies.

Detecting myocardial scar using electrocardiogram data and deep neural networks.

Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischaemic heart disease and can be detected with high diagnostic precision by magnetic resonance imaging.