A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease
SA Ebiaredoh-Mienye, TG Swart, E Esenogho… - Bioengineering, 2022 - mdpi.com
The high prevalence of chronic kidney disease (CKD) is a significant public health concern
globally. The condition has a high mortality rate, especially in developing countries. CKD …
globally. The condition has a high mortality rate, especially in developing countries. CKD …
An efficient early detection of diabetic retinopathy using dwarf mongoose optimization based deep belief network
In general, diabetic retinopathy (DR) is a common ocular disease that causes damage to the
retina due to blood leakage from the vessels. Earlier detection of DR becomes a …
retina due to blood leakage from the vessels. Earlier detection of DR becomes a …
HDLNET: a hybrid deep learning network model with intelligent IoT for detection and classification of chronic kidney disease
K Venkatrao, S Kareemulla - IEEE Access, 2023 - ieeexplore.ieee.org
Over 10% of the world's population now suffers from chronic kidney disease (CKD), and
millions die yearly. CKD should be detected early to extend the lives of those suffering and …
millions die yearly. CKD should be detected early to extend the lives of those suffering and …
Mpcitl: design of an efficient multimodal engine for pre-emptive identification of ckd via incremental transfer learning on clinical data samples
Abstract Chronic Kidney Disease (CKD) can be identified via MRI (Magnetic Resonance
Imaging) Scans, CT (Computerized Tomography) Scans, and clinical parameters including …
Imaging) Scans, CT (Computerized Tomography) Scans, and clinical parameters including …
An efficient and low complex model for optimal RBM features with weighted score-based ensemble multi-disease prediction
TP Anish, PM Joe Prathap - Computer Methods in Biomechanics …, 2023 - Taylor & Francis
Multi-disease prediction is regarded as the capacity to simultaneously identify various
diseases that are expected to be affected an individual at a certain period. These multiple …
diseases that are expected to be affected an individual at a certain period. These multiple …
[PDF][PDF] Prediction of chronic kidney disease with Machine Learning models and feature analysis using SHAP
Y Surekha, KR Kodepogu, GL Kumari… - Revue d'Intelligence …, 2023 - researchgate.net
Accepted: 5 April 2023 The world is significantly impacted by chronic kidney disease (CKD),
both in terms of the health and financial costs. CKD is becoming a bigger issue globally …
both in terms of the health and financial costs. CKD is becoming a bigger issue globally …
Chronic Kidney Disease Detection using AdaBoosting Ensemble Method and K-Fold Cross Validation
CKD (Chronic Kidney Disease) is among the most serious health issues worldwide. Among
the causes of total global mortality, chronic kidney disease ranked 27th in the Global Burden …
the causes of total global mortality, chronic kidney disease ranked 27th in the Global Burden …
An efficient IoT-artificial intelligence-based chronic kidney diseases prediction using temporal convolutional network (TCN) deep learning method in healthcare …
RS Gopi, TV Rao, UM Sethuramasamy… - … in Applied Sciences …, 2023 - semarakilmu.com.my
IOT (Internet of Things) can control the remote based patient's health care monitoring system
and here monitoring for the chronic kindney diseases predication levels. When an IoT …
and here monitoring for the chronic kindney diseases predication levels. When an IoT …
Multilevel Ensemble Method to Identify Risks in Chronic Kidney Disease Using Hybrid Synthetic Data
K Shouryadhar, PK Rao… - 2022 13th International …, 2022 - ieeexplore.ieee.org
This research was conducted with the goals of developing models that have an accurate
classification of chronic kidney disease (CKD) and locating significant prognostic factors …
classification of chronic kidney disease (CKD) and locating significant prognostic factors …
An effective role-oriented binary Walrus Grey Wolf approach for feature selection in early-stage chronic kidney disease detection
In clinical decision-making for chronic disorders like chronic kidney disease, high variability
often leads to uncertainty and negative outcomes. Deep learning techniques have been …
often leads to uncertainty and negative outcomes. Deep learning techniques have been …