Objective This study aimed to evaluate the prevalence and predictors of cardiovascular disease (CVD), chronic kidney disease ...
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Neural network cost functions: Which to use and why?
In this video, we will see what is Cost Function, what are the different types of Cost Function in Neural Network, and which ...
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Supervised learning made easy: Real-world example explained
In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...
Background Up to half of patients with infective endocarditis (IE) require cardiac surgery. Although anaemia is common, its precise prevalence, transfusion practices and impact on outcomes in ...
Background Despite anticoagulation, patients with atrial fibrillation (AF) experience persistent elevated cardiovascular risk ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Background Malnutrition influences prognosis in patients with heart failure, but current nutritional evaluation methods are ...
Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
Background The likelihood of HIV acquisition is increased following forced vaginal sex. This relates in part to ...
Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Abstract: In object detection, enhancing feature representation using localization information has been revealed as a crucial procedure to improve detection performance. However, the localization ...
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