Alzheimer’s Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes

There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine learning (ML) and image processing methods have been used to detect it. In this study, we used ML methods to classify AD using image and gene expression data. First, SpinalNet and convolutional neural network (CNN) were used to classify AD from MRI images. Then we used microarray gene expression data to classify the diseases using k-nearest neighbors (KNN), support vector classifier (SVC), and Xboost classifiers. Previous approaches used only either images or gene expression, while we used both data together and also explained the results…