A number of machine learning models have been applied to a prediction or classification task of diabetes. These models either tried to categorise patients into insulin and non-insulin, or anticipate the patients’ blood surge rate. Most medical experts have realised that there is a great relationship between patient’s symptoms with some chronic diseases and the blood sugar rate. This paper propo...

Live bird markets (LBMs) are at risk of contamination with the avian influenza H5N1 virus. There are a number of methods for prioritizing LBMs for intervention to curb the risk of contamination. Selecting a method depends on diagnostic objective and disease prevalence. In a low resource setting, options for prioritization are constricted by the cost of and resources available for tool developme...

Recent studies suggest that the deregulation of pathways, rather than individual genes, may be critical in triggering carcinogenesis. The pathway deregulation is often caused by the simultaneous deregulation of more than one gene in the pathway. This suggests that robust gene pair combinations may exploit the underlying bio-molecular reactions that are relevant to the pathway deregulation and t...

This paper proposes a feature selection based classification method that can be applied to better accuracy in the Digital Radiographs (DR) for the identification of Inferior Alveolar Nerve Injury (IANI). Different conventional features based on the shape and EZW (Embedded Zero tree Wavelet) based texture features are extracted using different feature extraction techniques. Then, aggregate votin...

Schizophrenia is a severe mental disorder associated with wide spectrum of cognitive and neurophysiological dysfunctions. Early diagnosis still difficult based on the manifestation disorder. In this study, we have evaluated whether machine learning techniques can help in schizophrenia, proposed processing pipeline order to obtain classifiers schizophrenia resting state EEG data. We computed wel...

Modern speech recognition systems typically cluster triphone phonetic contexts using decision trees. In this paper we describe a way to build multiple complementary decision trees from the same data, for the purpose of system combination. We do this by jointly building the decision trees using an objective function that has an added entropy term to encourage diversity among the decision trees. ...