Artificial Intelligence for Sustainable Applications

1Predictive Models of Alzheimer’s Disease Using Machine Learning Algorithms – An Analysis

Karpagam G. R.¹*, Swathipriya M.¹, Charanya A. G.¹ and Murali Murugan²

¹Department of Computer Science and Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India

²Director of Engineering, Macy’s, Georgia, USA

Abstract

Alzheimer’s is a neurodegenerative dementia that occurs in people aged above 65, and there is a rapid growth in the amount of people suffering from it. Almost three out of four AD cases are undiagnosed. This paper comes with the view of identifying a predictive machine learning model for Alzheimer’s disease with the help of a minimally invasive blood-based biomarker. By comparing models of different algorithms of machine learning, we conclude that the model following the Random Forest algorithm has the highest efficiency in terms of predicting the positive AD cases with the highest AUC of the ROC curve (0.927).

Keywords: Machine learning, automated machine learning, Alzheimer’s disease

1.1 Introduction

In the 1950s many researchers attempted to build models that could interpret the world better than humans do. Then came the term “Machine Learning”-the concept by which the machine can learn and behave in the same way as humans do. Machine learning (ML) saw rapid developments in the late 1990s and in early 2000s and have found its applications across several different domains including healthcare. The introduction of ML in healthcare has been a breakthrough ...