A predictive method for hepatitis disease diagnosis using ensembles of neuro-fuzzy technique

Hepatitis is an inflammation of the liver, most commonly caused by a viral infection. Supervised data mining techniques have been successful in hepatitis disease diagnosis through a set of datasets. Many methods have been developed by the aids of data mining techniques for hepatitis disease diagnosis. The majority of these methods are developed by single learning techniques. In addition, these methods do not support the ensemble learning of the data. Combining the outputs of several predictors can result in improved accuracy in classification problems.
Source: Journal of Infection and Public Health - Category: International Medicine & Public Health Authors: Source Type: research