A Literature Review on Prediction of Chronic Diseases using Machine Learning Techniques
Author:
Affiliation:
1. Research Scholar, Institute of Computer Science and Information Science, Srinivas University, Mangalore, Karnataka, India
2. Research Professor, Institute of Computer Science & Information Science, Srinivas University, Mangalore– 575001, India.
Abstract
Publisher
Srinivas University
Subject
General Medicine
Reference102 articles.
1. Takagi, K., Kondo, S., Nakamura, K., & Takiguchi, M. (2014). Lesion type classification by applying machine-learning technique to contrast-enhanced ultrasound images. IEICE TRANSACTIONS on Information and Systems, 97(11), 2947-2954.
2. Sebastiani, F. (2002). Machine learning in automated text categorization. ACM computing surveys (CSUR), 34(1), 1-47.
3. Sinclair, C., Pierce, L., & Matzner, S. (1999, December). An application of machine learning to network intrusion detection. In Proceedings 15th Annual Computer Security Applications Conference (ACSAC'99), IEEE, 8(1), 371-377.
4. Ambekar, S., & Phalnikar, R. (2018, August). Disease risk prediction by using convolutional neural network. In 2018 Fourth international conference on computing communication control and automation (ICCUBEA) IEEE., 5(3), 1-5.
5. Chetty, N., Vaisla, K. S., & Patil, N. (2015, May). An improved method for disease prediction using fuzzy approach. In 2015 Second International Conference on Advances in Computing and Communication Engineering IEEE., 6(4), 568-572.
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