A Hybrid Expert System for Individualized Quantification of Electrical Status Epilepticus During Sleep Using Biogeography-Based Optimization

Abstract

Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying such EEG patterns is critical to the diagnosis of ESES. While most of the existing automatic ESES quantification systems ignore the morphological variations of the signal as well as the individual variability among subjects. To address these issues, this paper presents a hybrid expert system that dedicates to mimicking the decision-making process of clinicians in ESES quantification by taking the morphological variations, individual variability, and medical knowledge into consideration. The proposed hybrid system not only offers a general scheme that could propel a semi-auto morphology analysis-based expert decision model to a fully automated ESES quantification with biogeography-based optimization (BBO), but also proposes a more precise individualized quantification system to involve the personalized characteristics by adopting an individualized parameters-selection framework. The feasibility and reliability of the proposed method are evaluated on a clinical dataset collected from twenty subjects at Children'

Application of Forward Chaining Method, Certainty Factor, and Bayes Theorem for Cattle Disease

“…It integrates a morphological analysis-based expert decision model with biogeography-based optimization (BBO) for parameter selection. The system was evaluated based on clinical datasets and showed superior performance over existing methods [19]. The effectiveness of two advanced data mining techniques -bivariate statistics models (certainty factor (CF)) and machine learning models (random forest (RF)) for accurate gully head erosion susceptibility mapping using Dongzhi Loess Tableland in China comprises an example at a regional scale.…”