Improved dwarf mongoose optimization algorithm using novel nonlinear control and exploration strategies
S Fu, H Huang, C Ma, J Wei, Y Li, Y Fu - Expert Systems with Applications, 2023 - Elsevier
Abstract The Dwarf Mongoose Optimization Algorithm (DMO) is a popular metaheuristic
algorithm utilized to solve real-world problems. However, DMO has limitations such as slow …
algorithm utilized to solve real-world problems. However, DMO has limitations such as slow …
Dynamic coati optimization algorithm for biomedical classification tasks
Medical datasets are primarily made up of numerous pointless and redundant elements in a
collection of patient records. None of these characteristics are necessary for a medical …
collection of patient records. None of these characteristics are necessary for a medical …
Parameter estimation of ECM model for Li-Ion battery using the weighted mean of vectors algorithm
Accurate parameter estimation of the equivalent circuit model (ECM) for Li-Ion batteries
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …
(LiBs) allows for better behavior modeling and understanding. This is crucial for various …
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 …
Integrated metaheuristic algorithms with extreme learning machine models for river streamflow prediction
Accurate river streamflow prediction is pivotal for effective resource planning and flood risk
management. Traditional river streamflow forecasting models encounter challenges such as …
management. Traditional river streamflow forecasting models encounter challenges such as …
AI-based model for automatic identification of multiple sclerosis based on enhanced sea-horse optimizer and MRI scans
MG Khattap, M Abd Elaziz, HGEMA Hassan… - Scientific Reports, 2024 - nature.com
This study aims to develop an AI-enhanced methodology for the expedited and accurate
diagnosis of Multiple Sclerosis (MS), a chronic disease affecting the central nervous system …
diagnosis of Multiple Sclerosis (MS), a chronic disease affecting the central nervous system …
Improved Kepler Optimization Algorithm for enhanced feature selection in liver disease classification
Liver diseases represent a significant healthcare challenge, impacting millions globally and
posing complexities in diagnosis. To address this global health concern, this paper …
posing complexities in diagnosis. To address this global health concern, this paper …
Ensemble machine learning prediction of hyperuricemia based on a prospective health checkup population
Y Zhang, L Zhang, H Lv, G Zhang - Frontiers in Physiology, 2024 - frontiersin.org
Objectives: An accurate prediction model for hyperuricemia (HUA) in adults remain
unavailable. This study aimed to develop a stacking ensemble prediction model for HUA to …
unavailable. This study aimed to develop a stacking ensemble prediction model for HUA to …
Detection of Kidney Disease in X-Ray Images Using Machine Learning on MobileNetV3 CNN Model
Classifying kidney pictures or patient data according to various disease categories, such as
stages of chronic kidney disease (CKD), PKD, kidney stones, renal tumours, and other …
stages of chronic kidney disease (CKD), PKD, kidney stones, renal tumours, and other …
Kidney Disease X-Ray Image Classification Using a ResNet50V2 Model based Machine Learning Approach
The process of Kidney Disease Classification entails the categorization of kidney pictures or
patient data into several disease classifications, including but not limited to chronic kidney …
patient data into several disease classifications, including but not limited to chronic kidney …