Publications by authors named "N Jajcay"
One of the interesting aspects of EEG data is the presence of temporally stable and spatially coherent patterns of activity, known as microstates, which have been linked to various cognitive and clinical phenomena. However, there is still no general agreement on the interpretation of microstate analysis. Various clustering algorithms have been used for microstate computation, and multiple studies suggest that the microstate time series may provide insight into the neural activity of the brain in the resting state.
View Article and Find Full Text PDFCurrent advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight.
View Article and Find Full Text PDFPurpose: The incidence of acute myocardial infarctions (AMI) shows circadian variation typically peaking during morning hours with a decline at night. However, this variation does not occur in patients with diabetes mellitus (DM). The night's decline of AMI may be partially explained by melatonin-related platelet inhibition.
View Article and Find Full Text PDFArticle Synopsis
- Recent advances in machine learning enable better analysis of patient data to predict outcomes, particularly for cardiogenic shock (CS) in patients with acute coronary syndrome using the MIMIC III database.
- This study focuses on improving data quality through various imputation techniques to handle missing data, comparing methods like k-nearest neighbors and Multiple Imputation by Chained Equations.
- The final model demonstrated strong classification performance with a mean area under the curve of 0.805, suggesting the potential utility of this data processing pipeline for other predictive analytics in healthcare.
Objectives: Purpose of this study was to evaluate properties of apelin, a peptide detectable in peripheral blood, for atrial fibrillation (AF) detection in a diverse population of patients covering a broad spectrum from healthy to polymorbid patients.
Background: AF is the most common cardiac arrhythmia with constantly increasing incidence and prevalence. Currently available diagnostic tools do not provide sufficient detection rate.