Feature selection

Healthcare system

Preprocessor

Ant colony optimization algorithms

Economic growth

Data pre-processing

Data mining

Geodesy

Machine learning

Benchmark (surveying)

Artificial intelligence

Health care

Economics

Geography

Computer science

Expert system

Classifier (UML)

Scientific Reports

At present times, healthcare systems are updated with advanced capabilities like machine learning (ML), data mining and artificial intelligence to offer human with more intelligent and expert healthcare services. This paper introduces an intelligent prediction and classification system for healthcare, namely Density based Feature Selection (DFS) with Ant Colony based Optimization (D-ACO) algorithm for chronic kidney disease (CKD). The proposed intelligent system eliminates irrelevant or redundant features by DFS in prior to the ACO based classifier construction. The proposed D-ACO framework three phases namely preprocessing, Feature Selection (FS) and classification. Furthermore, the D-ACO algorithm is tested using benchmark CKD dataset and the performance are investigated based on different evaluation factors. Comparing the D-ACO algorithm with existing methods, the presented intelligent system outperformed the other methodologies with a significant improvisation in classification accuracy using fewer features.

Intelligent Diagnostic Prediction and Classification System for Chronic Kidney Disease