This chapter describes the application of an intelligent machine learning technique (Support Vector Machines, SVM) to diagnose the patients with sleep apnoea syndrome using Electrocardiogram (ECG) signal. Sleep apnoea syndrome is a medical condition caused by sleep apnoea which is defined as the cessation of breathing for short periods during sleep. First, the importance of early diagnosis and ...

This article presents a new vibration diagnostic method designed to (PM) machines with permanent magnets. Those devices are commonly used in small wind and water systems or vehicles drives. The author’s method is very innovative and unique. Specific structural properties of PM machines are used in this method electromotive force (EMF) generated due to vibrations. There was analysed number of pu...

Résumé. L’évolution incontournable des systèmes ubiquitaires et en particulier les systèmes machine-to-machine (M2M) provoque la complexité de la gestion de ce type de système. La conception d’un tel système autonome et sensible au contexte basé sur une architecture d’auto-adaptabilité représente une solution prometteuse. Cette architecture modifie le comportement du système en fonction des bes...

objectivethis study aimed to assess brain natriuretic peptide in early diagnose of cardiac function in children with congenital heart diseases.methodologythis study was performed on children with chd and healthy. severity of heart failure modified ross classification system was used for grouping patients in four classes. for all participants, height, weight and head circumference were measured....

The average acoustic power and intensity levels from diagnostic ultrasound machines at five major Hospitals in Benue State were measured using ultrasound power meter UPM-DT-10AV. The ultrasound machine at Christian Hospital Mkar, Immaculate Conception Hospital Makurdi, Federal Medical centre Makurdi, Myom Hospital Gboko and Lobi Specialist Hospital Makurdi were used for the research work. The u...

Attention deficits, among other cognitive deficits, are frequently observed in schizophrenia. Although valid and reliable neurocognitive tasks have been established to assess attention deficits in schizophrenia, the hierarchical value of those tests as diagnostic discriminants on a single-subject level remains unclear. Thus, much research is devoted to attention deficits that are unlikely to be...

Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation ...

This paper addresses diagnostic information fusion for situations where several diagnostic tools are used to estimate a single system state. These estimates will always disagree to some extent and it is the task of the fusion module to provide an estimate which is more reliable than the best of the diagnostic tools. To that end, a fusion process was developed which performs a weighted average o...

Applying machine learning in the health care domain has shown promising results in recent years. Interpretable outputs from learning algorithms are desirable for decision making by health care personnel. In this work, we explore the possibility of utilizing causal relationships to refine diagnostic prediction. We focus on the task of diagnostic prediction using discomfort drawings, and explore ...