Statistical classification

Electrical engineering

Health informatics

Feature selection

Pattern recognition (psychology)

Feature (linguistics)

Data classification

Economic growth

Operating system

Data mining

Curse of dimensionality

Machine learning

Engineering

Philosophy

Artificial intelligence

Informatics

Health care

Economics

Computer science

Linguistics

Dimensionality reduction

Process (computing)

Selection (genetic algorithm)

Egyptian Informatics Journal

Chronic Disease Prediction plays a pivotal role in healthcare informatics. It is crucial to diagnose the disease at an early stage. This paper presents a survey on the utilization of feature selection and classification techniques for the diagnosis and prediction of chronic diseases. Adequate selection of features plays a significant role for enhancing accuracy of classification systems. Dimensionality reduction helps in improving overall performance of machine learning algorithm. The application of classification algorithms on disease datasets yields promising results by developing adaptive, automated and intelligent diagnostic systems for chronic diseases. Parallel classification systems can be used to expedite the process and to enhance the computational efficiency of results. This work presents a comprehensive overview of various feature selection methods and their inherent pros and cons. We then analyze adaptive classification systems and parallel classification systems for chronic disease prediction.

Feature selection and classification systems for chronic disease prediction: A review