Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening

Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening

Objective: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vi...

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Bibliographic Details
Main Authors: Md. Rashed-Al-Mahfuz, Abedul Haque, Akm Azad, Salem A. Alyami, Julian M. W. Quinn, Mohammad Ali Moni
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Attribute selection
chronic kidney disease (CKD)
computer-aided diagnosis
explainable AI
machine learning (ML)
Online Access:https://ieeexplore.ieee.org/document/9405681/

Internet

https://ieeexplore.ieee.org/document/9405681/

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