Research Area: Machine Learning
The application of machine learning in the field of medical diagnosis is increasing gradually. This can be contributed primarily to the improvement in the classification and recognition systems used in disease diagnosis which is able to provide data that aids medical experts in early detection of fatal diseases and therefore, increase the survival rate of patients significantly. In this paper, we apply different classification algorithms, each with its own advantage on three separate databases of disease (Heart, Breast cancer, Diabetes) available in UCI repository for disease prediction. The feature selection for each dataset was accomplished by backward modeling using the p-value test. The results of the study strengthen the idea of the application of machine learning in early detection of diseases.
Keywords:
Disease Prediction
Wisconsin Breast Cancer Dataset
Classification algorithms
Diabetes
Heart Disease Dataset
Machine Learning
Author(s) Name: Pahulpreet Singh Kohli; Shriya Arora
Journal name:
Conferrence name: International Conference on Computing Communication and Automation (ICCCA)
Publisher name: IEEE
DOI: 10.1109/CCAA.2018.8777449
Volume Information:
