Generalizability of electroencephalographic interpretation using artificial intelligence: An external validation study.

Objective: The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings.

Seizure provocation in EEG recordings: A data-driven approach.

Objective: Recording seizures on video-EEG has a high diagnostic value. However, bilateral convulsive seizures constitute a risk for the patients. Our aim was to investigate the diagnostic yield and associated risks of provocation methods in short-term video-EEGs.

Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence.

Importance: Electroencephalograms (EEGs) are a fundamental evaluation in neurology but require special expertise unavailable in many regions of the world. Artificial intelligence (AI) has a potential for addressing these unmet needs. Previous AI models address only limited aspects of EEG interpretation such as distinguishing abnormal from normal or identifying epileptiform activity.

Duration of epileptic seizure types: A data-driven approach.

Objective: To determine the duration of epileptic seizure types in patients who did not undergo withdrawal of antiseizure medication.

Methods: From a large, structured database of 11 919 consecutive, routine video-electroencephalograpy (EEG) recordings, labeled using the SCORE (Standardized Computer-Based Organized Reporting of EEG) system, we extracted and analyzed 2742 seizures. For each seizure type we determined median duration and range after removal of outliers (2.

Implementing the SCORE system improves the quality of clinical EEG reading.

Objective: To assess whether implementing the freeware version of the SCORE EEG system (Standardized Computer-based Organized Reporting of EEG) leads to improvement in the quality of clinical EEG reading, and whether EEG reports in SCORE EEG are understood and accepted by the referring physicians.

Methods: We generated EEG reports in the conventional, free-text style and then using SCORE EEG, in consecutive patients referred to routine EEG. We used the Georgian translation in the SCORE EEG Free Edition.

EEG normal variants: A prospective study using the SCORE system.

Objective: To determine the prevalence and characteristics of normal variants in EEG recordings in a large cohort, and provide readers with typical examples of all normal variants for educational purposes.

Methods: Using the SCORE EEG system (Standardized Computer-Based Organized Reporting of EEG), we prospectively extracted EEG features in consecutive patients. In this dataset, we analyzed 3050 recordings from 2319 patients (mean age 38.

Effect of Continuous Positive Airway Pressure on Symptoms and Prevalence of Insomnia in Patients With Obstructive Sleep Apnea: A Longitudinal Study.

Objective: Obstructive sleep apnea (OSA) and insomnia are the two most common sleep disorders. Continuous positive airway pressure (CPAP) is considered first-line treatment for OSA. In the present study, we assess the effect of CPAP on symptoms and prevalence of insomnia in patients with OSA.

Photoparoxysmal response and its characteristics in a large EEG database using the SCORE system.

Objective: To characterize photoparoxysmal EEG response (PPR) using a standardized protocol of intermittent photic stimulation (IPS) and standardized definitions for PPR, classified into six types.

Methods: Using the SCORE system (Standardized Computer-Based Organized Reporting of EEG) we prospectively built a large database of standardized EEG annotations. In this study, we extracted the features related to PPR from the structured dataset consisting of 10,671 EEG recordings with IPS, from 7,188 patients.

Interrater agreement of classification of photoparoxysmal electroencephalographic response.

Our goal was to assess the interrater agreement (IRA) of photoparoxysmal response (PPR) using the classification proposed by a task force of the International League Against Epilepsy (ILAE), and a simplified classification system proposed by our group. In addition, we evaluated IRA of epileptiform discharges (EDs) and the diagnostic significance of the electroencephalographic (EEG) abnormalities. We used EEG recordings from the European Reference Network (EpiCARE) and Standardized Computer-based Organized Reporting of EEG (SCORE).

Visual EEG reviewing times with SCORE EEG.

Objective: Visual EEG analysis is the gold standard for clinical EEG interpretation and analysis, but there is no published data on how long it takes to review and report an EEG in clinical routine. Estimates of reporting times may inform workforce planning and automation initiatives for EEG. The SCORE standard has recently been adopted to standardize clinical EEG reporting, but concern has been expressed about the time spent reporting.

Prevalence of Parasomnias in Patients With Obstructive Sleep Apnea. A Registry-Based Cross-Sectional Study.

To assess the prevalence of parasomnias in relation to presence and severity of obstructive sleep apnea (OSA). We hypothesized higher parasomnia prevalence with higher OSA severity. The sample comprised 4,372 patients referred to a Norwegian university hospital with suspicion of OSA (mean age 49.

Standardized computer-based organized reporting of EEG: SCORE - Second version.

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper.

Regularized Linear Discriminant Analysis of EEG Features in Dementia Patients.

The present study explores if EEG spectral parameters can discriminate between healthy elderly controls (HC), Alzheimer's disease (AD) and vascular dementia (VaD) using. We considered EEG data recorded during normal clinical routine with 114 healthy controls (HC), 114 AD, and 114 VaD patients. The spectral features extracted from the EEG were the absolute delta power, decay from lower to higher frequencies, amplitude, center and dispersion of the alpha power and baseline power of the entire frequency spectrum.

Prevalence of excessive sleepiness is higher whereas insomnia is lower with greater severity of obstructive sleep apnea.

Purpose: The objective of the present study was to investigate the prevalence of insomnia and excessive sleepiness in relation to the presence and severity of obstructive sleep apnea (OSA).

Methods: The sample consisted of patients referred to a university hospital on suspicion of OSA. In total, 1115 patients with mean age of 48 years were studied.

EEG Spectral Features Discriminate between Alzheimer's and Vascular Dementia.

Alzheimer's disease (AD) and vascular dementia (VaD) present with similar clinical symptoms of cognitive decline, but the underlying pathophysiological mechanisms differ. To determine whether clinical electroencephalography (EEG) can provide information relevant to discriminate between these diagnoses, we used quantitative EEG analysis to compare the spectra between non-medicated patients with AD (n = 77) and VaD (n = 77) and healthy elderly normal controls (NC) (n = 77). We use curve-fitting with a combination of a power loss and Gaussian function to model the averaged resting-state spectra of each EEG channel extracting six parameters.

Unified EEG terminology and criteria for nonconvulsive status epilepticus.

The diagnosis of nonconvulsive status epilepticus (NCSE) relies largely on electroencephalography (EEG) findings. The lack of a unified EEG terminology, and of evidence-based EEG criteria, leads to varying criteria for and ability to diagnose NCSE. We propose a unified terminology and classification system for NCSE, using, as a template, the Standardised Computer-based Organised Reporting of EEG (SCORE).

Standardized computer-based organized reporting of EEG: SCORE.

The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format.

[EEG--when and how?].

Background: Electroencephalography (EEG) is used for studying functional disorders of the brain. We provide an overview of the areas where EEG is most strongly indicated and the clinical benefit of the examination.

Method: This article is based on articles from personal literature archives and literature searches in PubMed, textbook on methods in clinical neurophysiology, the work of one of the authors on a new European standard for EEG and the authors' clinical experience.

Neurological features and enzyme therapy in patients with endocrine and exocrine pancreas dysfunction due to CEL mutations.

Objective: To further define clinical features associated with the syndrome of diabetes and pancreatic exocrine dysfunction due to mutations in the carboxyl-ester lipase (CEL) gene and to assess the effects of pancreatic enzyme substitution therapy.

Research Design And Methods: Nine patients with CEL gene mutation, exocrine deficiency, and diabetes were treated and followed for 30 months.

Results: Treatment improved symptoms in seven of nine patients.