利用机器学习技术预测早期肝病的智能模型

Taher M. Ghazal, Aziz Ur Rehman, Muhammad Saleem, Munir Ahmad, Shabir Ahmad, Faisal Mehmood
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引用次数: 92

摘要

肝病(LD)是世界范围内导致死亡的主要原因,影响着大量人群。多种因素影响肝脏,导致本病。这种疾病的诊断既昂贵又耗时。机器学习在自动疾病诊断方面提供了很大的潜力。因此,本研究的目的是评估各种机器学习(ML)算法通过预测来降低肝病诊断的高成本的功效。随着目前各种肝脏疾病的增加,早期发现肝脏疾病比以往任何时候都更加重要。本研究提出了利用机器学习技术预测肝脏疾病的智能模型。该模型的准确率为0.884,缺失率为0.116,性能更为有效和全面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Model to Predict Early Liver Disease using Machine Learning Technique
Liver Disease (LD) is the main cause of death worldwide, affecting a large number of people. A variety of factors affect the liver, resulting in this disease. The diagnosis of this condition is both expensive and time-consuming. Machine Learning offers a lot of potential in terms of automated disease diagnosis. As a result, the purpose of this research is to assess the efficacy of various Machine Learning (ML) algorithms to lower the high cost of liver disease diagnosis through prediction. With the current rise in numerous liver disorders, it’s more important than ever to detect liver disease early on. This research proposed intelligent model to predict liver disease using machine learning technique. This proposed model is more effective and comprehensive in terms of performance of 0.884 accuracy, and 0.116 miss-rate.
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