Random forest

Algorithm

Biology

Identification (biology)

Support vector machine

Statistical classification

Computer science

Botany

Naive Bayes classifier

Artificial intelligence

Decision tree

Cluster analysis

Logistic regression

Machine learning

Journal of Applied Science and Technology Trends

Nowadays, machine learning algorithms have become very important in the medical sector, especially for diagnosing disease from the medical database. Many companies using these techniques for the early prediction of diseases and enhance medical diagnostics. The motivation of this paper is to give an overview of the machine learning algorithms that are applied for the identification and prediction of many diseases such as Naïve Bayes, logistic regression, support vector machine, K-nearest neighbor, K-means clustering, decision tree, and random forest. In this work, many previous studies were reviewed that used machine learning algorithms for detecting various diseases in the medical area in the last three years. A comparison is provided concerning these algorithms, assessment processes, and the obtained results. Finally, a discussion of the previous works is presented.

The Role of Machine Learning Algorithms for Diagnosing Diseases