A robust chronic kidney disease classifier using machine learning
Clinical support systems are affected by the issue of high variance in terms of chronic
disorder prognosis. This uncertainty is one of the principal causes for the demise of large …
disorder prognosis. This uncertainty is one of the principal causes for the demise of large …
[PDF][PDF] Utilisation of machine learning techniques in testing and training of different medical datasets
On our planet, chemical waste increases day after day, the emergence of new types of it, as
well as the high level of toxic pollution, the difficulty of daily life, the increase in the …
well as the high level of toxic pollution, the difficulty of daily life, the increase in the …
Evolutionary algorithm for improving decision tree with global discretization in manufacturing
S Jun - Sensors, 2021 - mdpi.com
Due to the recent advance in the industrial Internet of Things (IoT) in manufacturing, the vast
amount of data from sensors has triggered the need for leveraging such big data for fault …
amount of data from sensors has triggered the need for leveraging such big data for fault …
Cost-sensitive ensemble feature ranking and automatic threshold selection for chronic kidney disease diagnosis
Automated medical diagnosis is one of the important machine learning applications in the
domain of healthcare. In this regard, most of the approaches primarily focus on optimizing …
domain of healthcare. In this regard, most of the approaches primarily focus on optimizing …
Implementation of Discretisation and Correlation-based Feature Selection to Optimize Support Vector Machine in Diagnosis of Chronic Kidney Disease
DAA Pertiwi, PR Setyorini, MA Muslim… - Buletin Ilmiah Sarjana …, 2023 - journal2.uad.ac.id
This study aims to improve the accuracy of the classification algorithm for diagnosing chronic
kidney disease. There are several models of data mining. In classification, the Support …
kidney disease. There are several models of data mining. In classification, the Support …
Prediction of Kidney Disease Utilizing a Hybrid Deep Learning Methodology
V Nallarasan, V Ponnusamy… - … and Control (IC4), 2024 - ieeexplore.ieee.org
The kidney is an essential organ inside the human body, playing a crucial role in several
physiological processes. One of its primary roles is the filtration of waste products and …
physiological processes. One of its primary roles is the filtration of waste products and …
Chronic Kidney Disease Detection Using Machine Learning Regression Models
B Singh, K Arora, SS Iyer - ECS Transactions, 2022 - iopscience.iop.org
The database of developments in the health sector is growing very rapidly. The data is very
important to be processed and needs to be useful. Machine Learning and data mining are …
important to be processed and needs to be useful. Machine Learning and data mining are …
[PDF][PDF] A genetic algorithm-based feature selection approach for diabetes prediction
K Kangra, J Singh - Int J Artif Intell, 2024 - pdfs.semanticscholar.org
Genetic algorithms have emerged as a powerful optimization technique for feature selection
due to their ability to search through a vast feature space efficiently. This study discusses the …
due to their ability to search through a vast feature space efficiently. This study discusses the …
Predicting chronic kidney disease using machine learning
The kidney is a vital organ of the body. The function of kidney is to filter the blood in the
body. When the kidneys filter blood, urine is made from excess and excess fluid in the body …
body. When the kidneys filter blood, urine is made from excess and excess fluid in the body …
[PDF][PDF] Performance prediction of learning programming-machine learning approach
RSOSTW AU - … of the 30th International Conference on …, 2022 - icce2022.apsce.net
Teaching and learning programming is a challenge faced by many educational institutions.
In this paper we described using machine learning with data mining techniques to predict …
In this paper we described using machine learning with data mining techniques to predict …