A new expert system for pediatric respiratory diseases by using neural networks

摘要: The successful application of data mining in highly visible fields like e-business and marketing have led to the popularity its use knowledge discovery databases (KDD) other industries sectors. Among these sectors that are just discovering medicine public health. medical collect huge amounts healthcare which, unfortunately, not "mined" discover hidden information. We can describe this as being 'information rich' yet 'knowledge poor'. In study, we briefly examine most important techniques such Artificial Neural Network massive volume field which is pediatric respiratory disease. Using symptoms dry cough, productive fever, heamoptysis, tachypnea, dysnea etc. Also using doctor sign bronchial breathing, chest pain, clubbing finger, crepitation, ronchi, cyanosis, decrease brearthing sound on auscultation, dullness percussion, hyper resonant inability swallow, mucopurelent sputum, pleural rub, distress, sputum (white), stridor, upper infection, wheezing, X-ray [showing lung consolidation], [shawing edematous epiglottic], subglottic narrowing classic narrow trachea], hypertanslucent lung], lobar collapse (increase) bronchovascular marking], diffuse haziness], it predict likelihood patients getting a They enable significant knowledge, e.g. patterns, relationships between factors related disease, be established.