Athanasios Tsanas

TL;DR: In this article, a statistical machine learning framework was developed to study the effect of eight input variables (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, etc.) on two output variables, namely heating load (HL) and cooling load (CL), of residential buildings.

TL;DR: It is found that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects, and are seen as an important step toward noninvasive diagnostic decision support in PD.

TL;DR: In this paper, the authors demonstrate rapid, remote replication of UPDRS assessment with clinically useful accuracy (about 7.5 points difference from the clinicians' estimates), using only simple, self-administered and noninvasive speech tests.

TL;DR: This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests, and proposes a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches.

TL;DR: The implementation of an hs-cTnI assay was evaluated in consecutive patients who had been admitted to the hospitals' emergency departments with suspected acute coronary syndrome and its findings question whether the diagnostic threshold for myocardial infarction should be based on the 99th centile derived from a normal reference population.