An Alzheimerâ€™s Disease Prediction System using Fuzzy Logic
Gayathri, D. S, Nagarajan, M
Journal of Intelligent Computing, Vol. 10, No. 4, 2019.
DOI: https://doi.org/10.6025/jic/2019/10/4/137-149
Link: http://www.dline.info/jic/fulltext/v10n4/jicv10n4_3.pdf
Abstract:
Information Technology has modernized the approaches of the investigation done by the medical researchers
as well as the experts in the clinical practice. Recent medical tools allow recording of massive volumes of patient data, which paves the way to know about the disease thoroughly and it helps for better healthcare measurements. But the medical experts in the clinical practice are unable to get benefit from the massive volumes of patient data. Thus there is a need for the computer based techniques, which supports the medical experts while making the diagnostic decisions. Thus the decision support system provides an intelligent report about the patient status based on the symptoms, lab reports and patient related information. Such Decision Support system helps to enhance the patient healthcare measures automatic based on knowledge discovery. Thus, this paper developed a software tool to validate the clinical data by implementing Fuzzy Logic method and data visualization methods for estimating the stages of the patient affected by the Alzheimerâ€™s disease. Here SAGE Test and ELISA test reports were used as biomarkers to analyze the stages of the Alzheimerâ€™s disease.