Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{145189,
        author = {D.VISHNU VARDHAN RAJU and DR. M.HUMERA KHANAM and A.KHUDHUS},
        title = {FEATURE EXTRACTION FOR DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {7},
        pages = {702-706},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145189},
        abstract = {Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficientand scalable machine learning algorithms for large-scale applications.The machine learning field has gained its momentum in almost any domain of research and just recently has become a reliable tool in the medical domain .Machine Learning(ML) is envisioned as a tool by which computer-based systems can be integrated in the health care field in order to get more efficient medical care.An ML-based methodology is described to build an application that is capable of identifying disseminating health care information.It extracts sentences from published medical papers that mention diseases and treatments, and identifies semantic relations that exist between diseases and treatments.In this paper we have focused onMachine Learning (ML) techniques and the Classification algorithms that are suitable to use for identifying and classifying relevant medical information in short texts.The encouraging results of our experiments validate the efficiency of the proposed techniques.},
        keywords = {BigdataAnalytics, Machine Learning,Health Care.},
        month = {},
        }