Learning-based screening of endothelial dysfunction from photoplethysmographic signals

Endothelial-Dysfunction (ED) screening is of primary importance to early diagnosis cardiovascular diseases. Recently, approaches to ED screening are focusing more and more on photoplethysmography (PPG)-signal analysis, which is performed in a threshold-sensitive way and may not be suitable for tackling the high variability of PPG signals. The goal of this work was to present an innovative machine-learning (ML) approach to ED screening that could tackle such variability. Two research hypotheses guided this work: (H1) ML can support ED screening by classifying PPG features; and (H2) classification performance can be improved when including also anthropometric features. To investigate H1 and H2, a new dataset was built from 59 subject. The dataset is balanced in terms of subjects with and without ED. Support vector machine (SVM), random forest (RF) and k-nearest neighbors (KNN) classifiers were investigated for feature classification. With the leave-one-out evaluation protocol, the best classification results for H1 were obtained with SVM (accuracy = 71%, recall = 59%). When testing H2, the recall was further improved to 67%. Such results are a promising step for developing a novel and intelligent PPG device to assist clinicians in performing large scale and low cost ED screening

Machine learning-based approaches to analyse and improve the diagnosis of endothelial dysfunction

Endothelial Dysfunction is achieving increasing importance, because it is strictly related to cardiovascular risks and it provides important prognostic data in addition to the classical ones. This paper introduces a machine learning approach for predicting Endothelial Dysfunction. The approach was applied and tested on a newly collected dataset, 'Endothelial Dysfunction Dataset (EDD)' and several machine learning algorithms are compared. This method comprises features related to the anthropometric or pathological characteristics of the analysed subjects. The experiments yield high accuracy, demonstrating the effectiveness and suitability of the proposed approach

Confidentiality of correspondence with counsel as a requirement of a fair trial in Italy

Analisi critica della disciplina normativa, alla luce dei principi costituzionali e convenzionali, del diritto di difesa dell’imputato nel processo penale, con particolare riguardo al rapporto con il difensore e alla tutela della riservatezz