Cognitive Artificial Intelligence Decision Support System based on Knowledge Growing System - A D W Sumari, C O Sereati, I N Syamsiana, M N Wibisono, R Abdulharis, D R H Putra (International Journal of Advanced Science and Technology, 2020)
Accurate and faster decision making has been a challenge for systems based onArtificial Intelligence (AI). Since its emergence in the middle of 20th century, there hasbeen a fast development in AI methods for decision making. The most often approachesused for decision making are from machine learning families such as support vectormethod (SVM), artificial neural network (ANN), k-nearest neighbor (kNN), Decision Tree,and naive Bayes (NB), which are based on supervised learning mechanism. The mainproblem in supervised learning is it needs many data or training set to be learnt duringtraining phase. If the number of training set is not sufficient, the accuracy will be low, andthis will be dangerous to be used as the basis for making decisions. In this paper, wepropose a new approach for accurate and faster decision making by using a technologyfrom Cognitive Artificial Intelligence (CAI) domain called as Knowledge Growing System(KGS). It has advantage to process multi-feature multi-label data which can be able todeliver more accurate and faster result. We also give an example of its usage inhealthcare application, especially for medical diagnosis.