Epilepsy Diagnosis from EEG Signals Using Continuous Wavelet Transform-Based Depthwise Convolutional Neural Network Model.

Epilepsy is a prevalent neurological disorder characterized by seizures that significantly impact individuals and their social environments. Given the unpredictable nature of epileptic seizures, developing automated epilepsy diagnosis systems is increasingly important. Epilepsy diagnosis traditionally relies on analyzing EEG signals, with recent deep learning methods gaining prominence due to their ability to bypass manual feature extraction.

A Comprehensive CNN Model for Age-Related Macular Degeneration Classification Using OCT: Integrating Inception Modules, SE Blocks, and ConvMixer.

: Age-related macular degeneration (AMD) is a significant cause of vision loss in older adults, often progressing without early noticeable symptoms. Deep learning (DL) models, particularly convolutional neural networks (CNNs), demonstrate potential in accurately diagnosing and classifying AMD using medical imaging technologies like optical coherence to-mography (OCT) scans. This study introduces a novel CNN-based DL method for AMD diagnosis, aiming to enhance computational efficiency and classification accuracy.

Sex differences in clinical and polysomnographic features of obstructive sleep apnea: The Turkish sleep apnea database (TURKAPNE) cohort.

Background: Previous reports from relatively small clinical cohorts have suggested that the clinical presentation of obstructive sleep apnea (OSA) differs between men and women.

Objective: We aimed to explore sex differences in clinical and polysomnographic features of OSA in a large nationwide registry.

Methods: Participants from the ongoing Turkish Sleep Apnea Database (TURKAPNE) Study from 34 centers were included in the current analysis.

Enhanced Panoramic Radiograph-Based Tooth Segmentation and Identification Using an Attention Gate-Based Encoder-Decoder Network.

Background: Dental disorders are one of the most important health problems, affecting billions of people all over the world. Early diagnosis is important for effective treatment planning. Precise dental disease segmentation requires reliable tooth numbering, which may be prone to errors if performed manually.

Temporal trajectory and left ventricular ejection fraction association of eight circulating biomarkers in first acute myocardial infarction patients: a 12-month prospective cohort study.

Aims: Our study aimed to explore the temporal trajectory of eight circulating biomarkers, measured serially over 12 months, in a prospective observational cohort of patients with acute myocardial infarction (AMI) and to investigate the association between these biomarkers and left ventricular ejection fraction (LVEF) during follow-up assessments.

Methods And Results: We enrolled 155 patients admitted for a first AMI requiring percutaneous coronary intervention (PCI). Baseline characteristics, laboratory test results, and cardiac ultrasound examinations were collected at pre-PCI (H0), immediately post-PCI (H24), at discharge (D3), and at 6 months (M6) and 12 months (M12) post-PCI.