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@article{155701,
        author = {kajal shah and Harsha Talele and Tanuja Patil and Jyoti Shirole and Pooja Bhavsar},
        title = {Liver Disease Prediction using Machine learning Algorithms},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {0-0},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155701},
        abstract = {Diseases related to the liver and heart are becoming more and more familiar with time. With continuous technological advancements, these will only increase in the future. Although people are becoming more conscious of health nowadays and are joining yoga classes and dance classes, still the sedentary lifestyle and luxuries that are continuously being introduced and enhanced, the problem is going to last long. Population ageing and the increase of chronic conditions incidence and prevalence produce a higher risk of hospitalization or death due to liver disease. This is exceptionally high for patients with multi-morbidity, leading to significant resource consumption. The most crucial challenge is to identify possible high-risk patients to improve health care service provision and also to reduce costs. Nowadays, population health management, based on intelligent models, can be used to assess the risk and identify these “complex” patients infected with liver disease},
        keywords = {DT Algorithms, KNN Algorithms, Liver Disease, MLP Classifier, SVM Algorithms},
        month = {},
        }