A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...
Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...
Abstract: The rising global cases of pulmonary diseases require new diagnostic methods beyond traditional techniques because they depend on subjective human analysis which proves inefficient to the ...
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 ...
How recommendations evolved from star ratings to behavioral data, and why the system may be worth billions as it scales to 325 million viewers ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Abstract: Accurate classification of coffee varieties is essential for ensuring product quality, supporting traceability, and maintaining consistency in the coffee industry. This study presents a deep ...
Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
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