Transcranial magnetic stimulation procedures use a magnetic field to carry a short-lasting electrical current pulse into the brain, where it stimulates neurons, particularly in superficial regions of the cerebral cortex. ...

We researched cross-modal statistical learning conducting to experiments: a behavioural one and a neuroimaging one. In the analysis of the later we used neural decoding with temporal generalization.

Despite the increasing capabilities of computers to master sophisticated human-like tasks and the recent explosive new wave of Machine Learning-based methods, the interior design field still remains a hard-to-master area, ...

Model interpretability is a problem for multivariate data in general and, very specifically, for dimensionality reduction techniques as applied to data visualization. The problem is even bigger for nonlinear dimensionality ...

This work attempts to identify biomarkers that can be used as indicators for mortality prediction in patients with shock. It uses machine learning techniques to analyze the clinical data, impute missing values in it, select ...

In many real-world application problems, the availability of data labels for supervised learning is rather limited. Incompletely labeled datasets are common in many of the databases generated in some of the currently most ...

G-Protein Coupled Receptors (GPCRs) are key players in cell- cell communication. They transduce a wide range of extracellular signals such as light, odors, hormones or neurotransmitters into ap- propriated cellular ...

The thesis examines how customers behavior helps to adjust a layout that optimizes sales. We designed ETL process that includes image processing, web scraping, followed by pattern mining, clustering, and NLP. Then, we ...

The management of the Intensive Care Unit (ICU) in a hospital has its own, very specific requirements that involve, amongst others, issues of risk-adjusted mortality and average length of stay; nurse turnover and communication ...