An ontology-based decision support system for nutrition deficiency

Abstract

Storing the patient's clinical test reports for analysis differs from clinic to clinic as most clinics store the details in customized software or freely available spreadsheets. In the nutrition test report, the test results show the levels, thresholds that doctors analyze and diagnose the type of deficiency. In many situations, the patients have a dilemma about the doctor's advice that results in a second opinion. Hence a simple decision support system is a necessity to help the doctor to analyze the laboratory test report data and prescribe the right treatment. This research proposes a nutrition deficiency decision support framework that models a biochemistry test report using an ontology and automatic nutrition deficiency classification. The resulting system is useful in hospitals for the automatic classification of nutritional deficiency.