ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals.

Background And Objectives: Electroencephalography (EEG) signals, often termed the letters of the brain, are one of the most cost-effective methods for gathering valuable information about brain activity. This study presents a new explainable feature engineering (XFE) model designed to classify EEG data for violence detection. The primary objective is to assess the classification capability of the proposed XFE model, which uses a next-generation feature extractor, and to obtain interpretable findings for EEG-based violence and stress detection.

Triglyceride-glucose index in patients with non-functioning adrenal incidentaloma, cortisol-secreting adrenal incidentaloma and healthy controls.

Objective: Cushing's syndrome increases the risk of cardiovascular disease. The triglyceride-glucose (TyG) index has been linked to an increased risk of cardiometabolic disorders. Whether patients with non-functioning adrenal incidentaloma (NFAI) or cortisol-secreting adrenal incidentaloma (CSAI) have altered TyG index is unknown.

Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals.

Electroencephalography (EEG) signals provide information about the brain activities, this study bridges neuroscience and machine learning by introducing an astronomy-inspired feature extraction model. In this work, we developed a novel feature extraction function, black-white hole pattern (BWHPat) which dynamically selects the most suitable pattern from 14 options. We developed BWHPat in a four-phase feature engineering model, involving multileveled feature extraction, feature selection, classification, and cortex map generation.

QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.

The most cost-effective data collection method is electroencephalography (EEG), which obtains meaningful information about the brain. Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress dataset has been collected, and an explainable feature engineering (XFE) model has been proposed using the Directed Lobish (DLob) symbolic language.

TATPat based explainable EEG model for neonatal seizure detection.

The most cost-effective data collection method is electroencephalography (EEG) to obtain meaningful information about the brain. Therefore, EEG signal processing is very important for neuroscience and machine learning (ML). The primary objective of this research is to detect neonatal seizures and explain these seizures using the new version of Directed Lobish.

Lobish: Symbolic Language for Interpreting Electroencephalogram Signals in Language Detection Using Channel-Based Transformation and Pattern.

Electroencephalogram (EEG) signals contain information about the brain's state as they reflect the brain's functioning. However, the manual interpretation of EEG signals is tedious and time-consuming. Therefore, automatic EEG translation models need to be proposed using machine learning methods.

Sedentary behavior and associated factors on admissions to internal medicine wards.

The relationship between sedentary lifestyle and chronic diseases is well known. This study examined the prevalence and factors associated with reduced physical activity (PA) among internal medicine inpatients on admission. In this single-center, cross-sectional study, inpatients aged 50 years or older were prospectively enrolled at a tertiary care facility in Ankara, Türkiye.

Clues for Facial Perceived Age: Exercise, Sun Protection, Photoaging, and Anthropometric Properties: An Observational Cross-Sectional Study.

Background And Objectives: The effect of environmental and genetic factors on the aging process is widely acknowledged. Yet, the extent to which each factor decisively contributes to the perception of looking younger or older remains a subject of debate. This study seeks to identify the factors linked to the perceived age among Turkish women.

The relationship of circulating MOTS-c level with liver fibrosis and metabolic components in patients with metabolic dysfunction-associated fatty liver disease.

Objective: Mitochondrial open reading frame of the 12s ribosomal RNA type-c (MOTS-c) is a novel identified mitochondrial signal transmission peptide that plays an important role in glucose, amino acid and lipid metabolism. In this study, we aimed to investigate the relationship of circulating MOTS-c level with noninvasive scores of fibrosis and the components of metabolic syndrome (MetS) in patients with metabolic dysfunction-associated fatty liver disease (MAFLD).

Patients And Methods: This was a single-center cross-sectional study, and the participants were divided into two groups based on their liver ultrasound results: the fatty liver group and the healthy control group.

[The Relationship of Enterotoxigenic Bacteroides fragilis and Fusobacterium nucleatum Intestinal Colonization with Colorectal Cancer: A Case-Control Study Performed with Colon Biopsies].

In recent years, it has been shown that some bacteria may be associated with colorectal cancer (CRC). In this study, it was aimed to investigate the role of Fusobacterium nucleatum and enterotoxigenic Bacteroides fragilis (ETBF) in the etiology of CRC by comparing the amounts of these bacteria in colon biopsy tissues of patients with CRC and healthy individuals. The amounts of F.

Clinical characteristics of adult and paediatric patients with familial hypercholesterolemia: A real-life cross-sectional study from the Turkish National Database.

Background And Aims: Familial hypercholesterolemia (FH) is the most common cause of premature atherosclerotic cardiovascular disease (ASCVD). Türkiye is among the countries with the highest rate of ASCVD. However, no population-based study has been published so far on the prevalence of FH, demographic and clinical characteristics, burden of ASCVD, treatment compliance, and attainment of low-density lipoprotein cholesterol (LDL-C) targets.

Geriatric syndromes in the population older than 90 years: The prevalence and association with chronic diseases.

Objective: The aim of this study was to explore the prevalence of geriatric syndromes and comorbid conditions, as well as their interrelationships, in individuals aged 90 years and over.

Methods: This study included participants aged 90 years and older who underwent a comprehensive geriatric assessment in a tertiary geriatric outpatient clinic. Demographic and clinical characteristics were obtained using the electronic medical records.

Critical questions in diabetes management: What are the most compelling challenges and how can we handle them?

Background: The prevalence of diabetes mellitus is growing worldwide, showing almost a 10-fold increase in the last five decades. Despite advances in the understanding of the disease mechanisms, preventive measures, and treatment options, morbidity and mortality remain high. Moreover, the burden of uncontrolled glycemia and associated complications have a significant impact on healthcare costs.

Assessment of clinical features and coexisting geriatric syndromes in newly diagnosed dementia with Lewy bodies: a retrospective study in a tertiary geriatrics setting in Turkey.

Purpose: Identifying the associated clinical conditions in patients with newly diagnosed dementia with Lewy bodies (DLB) may contribute to the disease management. This study aimed to examine the clinical features and coexisting geriatric syndromes of patients with newly diagnosed DLB.

Method: This cross-sectional study included newly diagnosed DLB participants who were admitted to a tertiary geriatric outpatient clinic.

The Clinical Characteristics and Outcomes of COVID-19 Patients with Pre-Existing Thyroid Dysfunction: A Nationwide Study.

To which extent the pre-existing hypothyroidism or hyperthyroidism has an impact on coronavirus infection 2019 (COVID-19) outcomes remains unclear. The objective of this study was to evaluate COVID-19 morbidity and mortality in patients with pre-existing thyroid dysfunction. A retrospective cohort of patients with a polymerase chain reaction (PCR)-confirmed COVID-19 infection (n=14 966) from March 11 to May 30, 2020, was established using the database of the Turkish Ministry of Health.

Clinical features and predisposing factors of delirium due to COVID-19 pneumonia in intensive care units.

Objective: Delirium is an acute disorder in which attention, perception, memory, thought, mood, psychomotor activity and sleep-wake cycles change rapidly. Delirium is also a common clinical syndrome in patients hospitalized in intensive care units due to COVID-19 pneumonia. We reviewed clinical features and predisposing factors of delirium according to psychomotor subtype in patients hospitalized in the intensive care units due to COVID-19 pneumonia.

Peripheral Vascular Disease is Associated with Impaired Activities of Daily Living in the Elderly with Dementia: A Prospective Study.

Background: Although distinct disorders, peripheral vascular disease (PVD) and dementia are both associated with a progressive decline in activities of daily living in elderly patients.

Objective: This study aimed to compare the functional performance scores between elderly patients with and without dementia and with or without PVD.

Methods: Patients with Alzheimer's disease, vascular dementia, and mixed type dementia and controls were prospectively enrolled.

Evaluation of neurological disorders that develop concurrently with COVID-19 pneumonia: a retrospective analysis.

Background: During the pandemic, many neurological symptoms have been evaluated as complications of COVID-19 pneumonia.

Objective: To investigate the frequency and characteristics of neurological findings, and their effects on the prognosis of patients with COVID-19 pneumonia who consulted with the Neurology department.

Methods: Data on 2329 patients who were hospitalized with the diagnosis of COVID-19 pneumonia in our hospital were scanned.