Early Diagnosis of Liver Disease Using Machine Learning Techniques

被引：0

作者：

Hegde, Nagaratna P. ^{[1
]}

Vikkurty, Sireesha ^{[1
]}

Sriperambuduri, Vinay Kumar ^{[1
]}

Gogune, Sruthi ^{[1
]}

Anish, Palabatla ^{[1
]}

Thanneru, Praneeth ^{[1
]}

机构：

[1] Vasavi Coll Engn, Dept CSE, Hyderabad, Telangana, India

来源：

PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON DATA SCIENCE, MACHINE LEARNING AND APPLICATIONS, VOL 1, ICDSMLA 2023 | 2025年 / 1273卷

关键词：

Data Analysis; Confusion Matrix; Data Streamlining; Correlation Matrix; False Negatives; Accuracy;

D O I：

10.1007/978-981-97-8031-0_120

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Liver diseases are a global health concern, and early diagnosis is crucial for effective treatment. While traditional liver-function laboratory tests provide valuable information, they may not say much about any emerging or underlying illnesses. In this study, we explore the efficacy of machine learning algorithms in predicting the risk of liver disease using the Indian Liver Patient Dataset. This could help patients concerned opt for timely and effective treatment.

引用

页码：1138 / 1143

页数：6

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