
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 7 Issue 3
May-June 2025
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Prediction of Liver Disease Using Machine Learning
Author(s) | Prof. K. K. Archana, Ms. Mahalakshmi R S, Ms. Narmatha Bharathi A, Ms. Reem A |
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Country | India |
Abstract | This study focuses on predicting liver disease using machine learning, highlighting the importance of accurate diagnosis and early detection. Through thorough data preprocessing—such as handling missing values, addressing class imbalance with SMOTE, and applying iterative imputation—a high-quality dataset is created. The performance of SVM, KNN, HVC, and Random Forest algorithms is evaluated, with Random Forest achieving an accuracy of 85%. Ultimately, this research makes a significant contribution to healthcare analytics by providing a systematic, data-driven framework for the diagnosis and management of liver disease. This research enhances data-driven decision support for timely and accurate liver disease diagnosis, ultimately improving patient outcomes. |
Field | Engineering |
Published In | Volume 7, Issue 3, May-June 2025 |
Published On | 2025-05-05 |
DOI | https://doi.org/10.36948/ijfmr.2025.v07i03.43872 |
Short DOI | https://doi.org/g9hskh |
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E-ISSN 2582-2160

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IJFMR DOI prefix is
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