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Published Paper Details:
Early Prediction of Eye Diseases using Machine Learning models and Ensemble techniques
Authors
Madhab Paul Choudhury,Jagannibas Paul Choudhury
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Keywords
machine learning models, Random forest, decision tree, gradient boosting, KNN(K nearest neighbor), Ensemble techniques, voting classifier using maximum voting, average voting, Blending, Bagging and boosting.
Abstract
Artificial Intelligence (AI) has changed something so that it becomes much better in various aspects of our lives, offering solutions to numerous problems and bridging gaps between reality and business. Within the domain of AI, emerging technologies such as machine learning and deep learning models have played an important role in transforming the way so that we can analyse data, make decisions, and can take action or give attention to difficult situations or problems, with an objective to understand them to find solutions.
Liver disease encompasses a wide range of conditions that impair the liver's ability to function properly, leading to serious health issues. Risk factors for liver disease include viral infections (e.g., hepatitis B and C), excessive alcohol consumption, obesity, metabolic disorders, and genetic predisposition. Symptoms vary depending on the disease's severity but commonly include fatigue, jaundice, abdominal pain, and swelling. If the lever disease can be detected in early life, certain preventive measures can be taken so that the patient can recover from lever disease and can enjoy a real and happy life.
Here machine learning models and ensemble methods of machine learning models have been applied for selecting a proper model for prediction of lever disease of the person. Under machine learning models Random forest, decision tree, gradient boosting, KNN(K nearest neighbour), logistic regression have been used. Under ensemble methods, voting classifier using maximum voting, average voting, Blending, Bagging and boosting, stacking of models have been used.
IJCRT's Publication Details
Unique Identification Number - IJCRT2512229
Paper ID - 298151
Author type - Indian Author
Page Number(s) - b912-b927
Pubished in - Volume 13 | Issue 12 | December 2025
DOI (Digital Object Identifier) -
No Of Downloads - 83
Author Country - India, -, -, -, -, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
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Madhab Paul Choudhury,Jagannibas Paul Choudhury, "Early Prediction of Eye Diseases using Machine Learning models and Ensemble techniques", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 12, pp.b912-b927, December 2025, Available at :http://www.ijcrt.org/papers/IJCRT2512229.pdf
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