Enhancing ensemble classifiers utilizing gaze tracking data for autism spectrum disorder diagnosis
RO da Silva Sá, G de Castro Michelassi… - Computers in Biology …, 2024 - Elsevier
Abstract Problem: Diagnosing Autism Spectrum Disorder (ASD) remains a significant
challenge, especially in regions where access to specialists is limited. Computer-based …
challenge, especially in regions where access to specialists is limited. Computer-based …
[HTML][HTML] ACD-ML: Advanced CKD detection using machine learning: A tri-phase ensemble and multi-layered stacking and blending approach
MF Hossain, ST Diya, R Khan - Computer Methods and Programs in …, 2025 - Elsevier
Abstract Chronic Kidney Disease (CKD), the gradual loss and irreversible damage of the
kidney's functionality, is one of the leading contributors to death and causes about 1.3 …
kidney's functionality, is one of the leading contributors to death and causes about 1.3 …
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 …
A Proposed Multilayer Perceptron Model and Kernel Principal Analysis Component for the Prediction of Chronic Kidney Disease
Abstract unfortunately, this stage is mostly detected at a late stage, leading to dialysis or
transplantation. Early detection is important for the effective management of CKD. ML has …
transplantation. Early detection is important for the effective management of CKD. ML has …
An Effective Identification of Tuberculosis in Chest X-rays Using Convolutional Neural Network Model
Tuberculosis (TB) continues to be a major global health concern, contributing significantly to
premature mortality rates around the globe. This research highlights the critical role that …
premature mortality rates around the globe. This research highlights the critical role that …
Early Prediction and Progrssion of Chronic Kidney Disease Using Machine Lerning Techniques
N Sonone, A Daniel - 2024 2nd International Conference on …, 2024 - ieeexplore.ieee.org
A serious medical condition is chronic kidney disease that necessitates early detection and
continuing monitoring to avoid harmful consequences. This report describes a …
continuing monitoring to avoid harmful consequences. This report describes a …
Combining Optical Sensing with Deep Learning for Enhanced Non-Invasive Kidney Function Measurement
G Divya, R Vasuki - 2024 First International Conference on …, 2024 - ieeexplore.ieee.org
The difficulty of non-invasive kidney function monitoring is addressed in the paper by using a
deep learning model that uses optical sensors to estimate Glomerular Filtration Rate (GFR) …
deep learning model that uses optical sensors to estimate Glomerular Filtration Rate (GFR) …
A Novel Ensembled Deep Machine Learning Framework for the Prediction of Chronic Disease
The state of the environment and human behaviour today contribute to a wide range of
diseases that affect people. To avoid such diseases reaching their worst, it is crucial to …
diseases that affect people. To avoid such diseases reaching their worst, it is crucial to …
Optimizing Chronic Kidney Disease Prediction: A Machine Learning Approach with Minimal Diagnostic Predictors
S Pechprasarn, P Wetchasit… - Journal of Current …, 2025 - ph04.tci-thaijo.org
Chronic kidney disease (CKD) is a major public health issue that necessitates accurate
diagnostic methods for effective management. This study involved training an open-source …
diagnostic methods for effective management. This study involved training an open-source …