Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
The new Instagram feature reveals what the algorithm thinks you like and lets you adjust it, reshaping how content gets recommended on Reels. Instagram launched Your Algorithm in the U.S. today, a ...
This study aimed to develop a predictive model for early PSD following TKA using ML algorithms, identify key predictive factors, and provide an interpretable model to guide clinical decision-making.
Rapid, accurate, and efficient prediction of surrounding rock grades is crucial for ensuring the safety and enhancing the efficiency of tunnel boring machine (TBM) construction. To achieve intelligent ...
Gradient Boost Enhanced Artificial Immune System Algorithm for Adaptive DDoS Attack Detection in IoT
Abstract: Distributed Denial of Service attacks (DDoS) targeting the Internet of Things (IoT) remain a pervasive cybersecurity challenge. Biologically inspired solutions have shown promise for DDoS ...
Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
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