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StudiuEpilepsieÎncredere bună22.06.2026

Simultaneous Bilateral Femoral Neck Fractures in a Pediatric Patient Caused by Epileptic Convulsions: A Case Report

A 13-year-old boy with epilepsy sustained simultaneous bilateral femoral neck fractures during an epileptic seizure, marking the first reported case of this injury pattern in pediatric epilepsy literature. The fractures were successfully treated with closed reduction, internal fixation, and ultrasound therapy, with bone union confirmed at 6 months, highlighting the importance of screening for fractures in children with post-seizure complaints.

StudiuEpilepsieÎncredere înaltă22.06.2026

Anti-seizure medication response and glymphatic system function in focal epilepsy: a DTI-ALPS study

This study examined glymphatic system function in 100 focal epilepsy patients versus 79 healthy controls using diffusion tensor imaging analysis along the perivascular space (DTI-ALPS). Poor responders to anti-seizure medication showed significantly lower DTI-ALPS indices compared to good responders, suggesting impaired glymphatic clearance may relate to medication resistance in focal epilepsy.

StudiuEpilepsieÎncredere bună22.06.2026

Dostoevsky's Epilepsy and its Portrayal in The Brothers Karamazov

Fyodor Dostoevsky, a 19th-century Russian novelist with epilepsy, incorporated his personal experience with seizure disorder into his novels, particularly in The Brothers Karamazov where he explores family dynamics and uses psychogenic non-epileptic seizures as a narrative element in the character Smerdyakov's criminal alibi.

StudiuEpilepsieÎncredere bună21.06.2026

Prediction of Epileptic Seizure Using Deep Learning Techniques

This study proposes a deep learning approach for predicting epileptic seizures using EEG signal analysis, employing convolutional neural networks for feature extraction and Bi-LSTM for classification. The method achieved 99.61% accuracy and aims to improve patient quality of life through early seizure detection and timely intervention.

StudiuEpilepsieÎncredere înaltă21.06.2026

Machine Learning Models for Predicting Anti-Seizure Medication Response in Epilepsy: A Systematic Review

This systematic review of 37 studies examines how machine learning models can predict individual patient responses to anti-seizure medications by analyzing clinical data, brain imaging, EEG, and genetic information. While some models show promising accuracy, results vary widely, and the field faces significant limitations related to data quality and quantity that require further research and standardization.

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