Improving Chronic Kidney Disease Detection Efficiency: Fine Tuned CatBoost and Nature-Inspired Algorithms with Explainable AI
Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality. Mitigation of progression of CKD and better...
Optimizing DDoS Detection in SDNs Through Machine Learning Models
The emergence of Software-Defined Networking (SDN) has changed the network structure by separating the control plane from the data plane. However, this innovation has also increased susceptibility...
A Modified VGG19-Based Framework for Accurate and Interpretable Real-Time Bone Fracture Detection
Early and accurate detection of the bone fracture is paramount to initiating treatment as early as possible and avoiding any delay in patient treatment and outcomes. Interpretation of X-ray image...
Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data
Due to the rapid growth in the number of Internet of Things (IoT) networks, the cyber risk has increased exponentially, and therefore, we have to develop effective IDS that can work well with...
MobileDenseAttn:A Dual-Stream Architecture for Accurate and Interpretable Brain Tumor Detection
The detection of brain tumor in MRI is an important aspect of ensuring timely diagnostics and treatment; however, manual analysis is commonly long and error-prone. Current approaches are not...
StackLiverNet: A Novel Stacked Ensemble Model for Accurate and Interpretable Liver Disease Detection
Liver diseases are a serious health concern in the world, which requires precise and timely diagnosis to enhance the survival chances of patients. The current literature implemented numerous...
A Lightweight and Explainable DenseNet-121 Framework for Grape Leaf Disease Classification
Grapes are among the most economically and culturally significant fruits on a global scale, and table grapes and wine are produced in significant quantities in Europe and Asia. The production and...