Classification of Diseases Using Machine Learning Algorithms: A Comparative Study

Marco-Antonio Moreno-Ibarra; Yenny Villuendas-Rey; Miltiadis D. Lytras; Cornelio Yáñez-Márquez; Julio-César Salgado-Ramírez

doi:10.3390/math9151817

journal article Open Access Jul 31, 2021

Classification of Diseases Using Machine Learning Algorithms: A Comparative Study

Marco-Antonio Moreno-Ibarra Yenny Villuendas-Rey

Miltiadis D. Lytras

Cornelio Yáñez-Márquez

Julio-César Salgado-Ramírez

Mathematics Vol. 9 No. 15 pp. 1817 · MDPI AG

View at Publisher Save 10.3390/math9151817

Abstract

Machine learning in the medical area has become a very important requirement. The healthcare professional needs useful tools to diagnose medical illnesses. Classifiers are important to provide tools that can be useful to the health professional for this purpose. However, questions arise: which classifier to use? What metrics are appropriate to measure the performance of the classifier? How to determine a good distribution of the data so that the classifier does not bias the medical patterns to be classified in a particular class? Then most important question: does a classifier perform well for a particular disease? This paper will present some answers to the questions mentioned above, making use of classification algorithms widely used in machine learning research with datasets relating to medical illnesses under the supervised learning scheme. In addition to state-of-the-art algorithms in pattern classification, we introduce a novelty: the use of meta-learning to determine, a priori, which classifier would be the ideal for a specific dataset. The results obtained show numerically and statistically that there are reliable classifiers to suggest medical diagnoses. In addition, we provide some insights about the expected performance of classifiers for such a task.

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Details

Published: Jul 31, 2021
Vol/Issue: 9(15)
Pages: 1817
License: View

Authors

M

Marco-Antonio Moreno-Ibarra

Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07700, Mexico

Y

Yenny Villuendas-Rey

Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07700, Mexico

M

Miltiadis D. Lytras

Effat College of Engineering, Effat University, P.O. Box 34689, Jeddah 21478, Saudi Arabia

C

Cornelio Yáñez-Márquez

Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City 07700, Mexico

J

Julio-César Salgado-Ramírez

Ingeniería Biomédica, Universidad Politécnica de Pachuca, Pachuca 43380, Mexico

Cite This Article

Marco-Antonio Moreno-Ibarra, Yenny Villuendas-Rey, Miltiadis D. Lytras, et al. (2021). Classification of Diseases Using Machine Learning Algorithms: A Comparative Study. Mathematics, 9(15), 1817. https://doi.org/10.3390/math9151817

Classification of Diseases Using Machine Learning Algorithms: A Comparative Study

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