Author:Javad Hassannataj Joloudari

Publications
EasyChair Preprint no. 7829
EasyChair Preprint no. 7645
EasyChair Preprint no. 6771
EasyChair Preprint no. 6173
EasyChair Preprint no. 6048
EasyChair Preprint no. 6330
EasyChair Preprint no. 2467
EasyChair Preprint no. 1824

Keyphrases

Artificial Intelligence2, breast cancer, breast cancer dataset, Breast Cancer Detection, cancer mass, Cloud Computing, Confusion Matrix, Convolutional Neural Networks, coronary artery disease2, coronary artery disease diagnosis, Coronary Heart Disease, COVID-19 Diagnosis, cross validation technique, CT scan images, Data Mining, Data Mining Technique, Deep Convolutional Neural Network, deep learning3, Deep Neural Network2, developed country, diagnosis, Edge Computing, Electrocardiogram, ELM model, elm rbf model, epithelial cell size, evaluation criterion, expert system, Extreme Learning Machine, Extreme Learning Machine (ELM), first module, fold cross, fuzzy c-means clustering, Fuzzy Linguistic Variable, fuzzy rule, fuzzy system, Genetic Algorithm, Health Informatics, Heart Disease, hybrid machine learning, image analysis, Internet of Things, linguistic variable, machine learning5, Malaria diagnosis, Malignant breast cancer, MobileViT2, multilayer fuzzy expert system, Myocardial Infarction Disease, negative rate, neural network2, prediction, Predictive Features, Radial Basis Function, Radial Basis Function (RBF), Reinforcement Learning, resource allocation, rmse r2 mape model, Support Vector Machine2, Support Vector Machine (SVM), Vision Transformers, Wisconsin Dataset.