Performance evaluation on machine learning classification techniques for disease classification and forecasting through data analytics for chronic kidney disease …
W Gunarathne, KDM Perera… - 2017 IEEE 17th …, 2017 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is considered as kidney damage which lasts longer than
three months. In Sri Lanka, CKD has become a severe problem in the present days due to …
three months. In Sri Lanka, CKD has become a severe problem in the present days due to …
Analysis of chronic kidney disease dataset by applying machine learning methods
Y Amirgaliyev, S Shamiluulu… - 2018 IEEE 12th …, 2018 - ieeexplore.ieee.org
Currently, there are many people in the world suffering from chronic kidney diseases
worldwide. Due to the several risk factors like food, environment and living standards many …
worldwide. Due to the several risk factors like food, environment and living standards many …
Boosted classifier and features selection for enhancing chronic kidney disease diagnose
MS Wibawa, IMD Maysanjaya… - 2017 5th international …, 2017 - ieeexplore.ieee.org
Chronic kidney disease (CKD) is a disease caused by degeneration function of the kidneys.
CKD is top ten leading causes of death in the world. There are two leading causes of CKD …
CKD is top ten leading causes of death in the world. There are two leading causes of CKD …
Predictive analytics for chronic kidney disease using machine learning techniques
A Charleonnan, T Fufaung… - 2016 management …, 2016 - ieeexplore.ieee.org
Predictive analytics for healthcare using machine learning is a challenged task to help
doctors decide the exact treatments for saving lives. In this paper, we present machine …
doctors decide the exact treatments for saving lives. In this paper, we present machine …
Role of attributes selection in classification of Chronic Kidney Disease patients
In the present days the Chronic Kidney Disease (CKD) is a common problem to the public.
CKD is generally considered as kidney damage and is usually measured with the GFR …
CKD is generally considered as kidney damage and is usually measured with the GFR …
Prediction performance of individual and ensemble learners for chronic kidney disease
DS Sisodia, A Verma - 2017 international conference on …, 2017 - ieeexplore.ieee.org
Automating the process of predicting diseases prove assistive and time-saving for a
practitioner in the field of medical diagnosis. The accurate prediction of any disease not only …
practitioner in the field of medical diagnosis. The accurate prediction of any disease not only …
Optimal feature selection for chronic kidney disease classification using deep learning classifier
K Shankar, P Manickam, G Devika… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is an increasing failure of kidney function leading to kidney
failure over the years. The disease settles down and hence makes its diagnosis difficult …
failure over the years. The disease settles down and hence makes its diagnosis difficult …
Detection of chronic kidney disease and selecting important predictive attributes
A Salekin, J Stankovic - 2016 IEEE International Conference on …, 2016 - ieeexplore.ieee.org
Chronic kidney disease (CKD) is a major public health concern with rising prevalence. In
this study we consider 24 predictive parameters and create a machine learning classifier to …
this study we consider 24 predictive parameters and create a machine learning classifier to …
Predicting chronic kidney disease using machine learning algorithms
In the modern era, everyone tries to be aware of their health, but because of their workload
and hectic schedules, they only pay attention to it when certain symptoms appear. However …
and hectic schedules, they only pay attention to it when certain symptoms appear. However …
Predictive Machine Learning Approaches for Chronic Kidney Disease
It might be challenging to diagnose chronic kidney disease (CKD) in its early stages due to
the lack of symptoms. The creation and validation of a predictive model for the prognosis of …
the lack of symptoms. The creation and validation of a predictive model for the prognosis of …