Comparative Analysis of Machine Learning Techniques in Health System
Olubukola Emmanuel Olawade, Adebukola Onashoga, Oluwasefunmi 'Tale Arogundade · 2020
Medical diagnosis is a complicated task and plays a vital role in saving human lives so it needs to be executed accurately and efficiently. An appropriate and accurate computer based automated decision support system is required to reduce cost for achieving clinical tests. Machine learning (ML) techniques have become important to support decision making. In this paper, we present an evaluation and comparison of various machine learning techniques which has emerged in recent years. The result shows descriptive statistics of frequency of various machine learning techniques. Of all the ML techniques under the review, Random Forest (RF) has the highest of frequency of usage.