Research Area:  Machine Learning

Abstract:

Accurate prediction of diabetes is an important issue in health prognostics. However, data overfitting degrades the prediction accuracy in diabetes prognosis. In this paper, a reliable prediction system for the disease of diabetes is presented using a dropout method to address the overfitting issue. In the proposed method, deep learning neural network is employed where fully connected layers are followed by dropout layers. The proposed neural network outperforms other state-of-art methods in better prediction scores for the Pima Indians Diabetes Data Set.

Keywords:  

Author(s) Name:  Akm Ashiquzzaman, Abdul Kawsar Tushar, Md. Rashedul Islam, Dongkoo Shon, Kichang Im, Jeong-Ho Park, Dong-Sun Lim & Jongmyon Kim

Publisher name:  Springer

DOI:  10.1007/978-981-10-6451-7_5

Volume Information:  

Paper Link:   https://link.springer.com/chapter/10.1007/978-981-10-6451-7_5