The possible role of machine learning in detection of increased cardiovascular risk patients - KSC MR Study (design).

Introduction: Currently, just a few major parameters are used for cardiovascular (CV) risk quantification to identify many of the high-risk subjects; however, they leave a lot of them with an underestimated level of CV risk which does not reflect the reality.

Material And Methods: The submitted study design of the Kosice Selective Coronarography Multiple Risk (KSC MR) Study will use computer analysis of coronary angiography results of admitted patients along with broad patients' characteristics based on questionnaires, physical findings, laboratory and many other examinations.

Results: Obtained data will undergo machine learning protocols with the aim of developing algorithms which will include all available parameters and accurately calculate the probability of coronary artery disease.

Recent Advances in ASIC Development for Enhanced Performance M-Sequence UWB Systems.

Short-range ultra-wideband (UWB) radar sensors belong to very promising sensing techniques that have received vast attention recently. The M-sequence UWB sensing techniques for radio detection and ranging feature several advantages over the other short-range radars, inter alia superior integration capabilities. The prerequisite to investigate their capabilities in real scenarios is the existence of physically available hardware, i.