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Linking leaf traits to light: A new framework for predicting canopy optical behavior

A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that ...
IEEE

Analysis of Decision Tree and Random Forest Algorithms for Nutrient Deficiency Classification in Citrus Leaves through Image Processing

Abstract: The research presents a hybrid approach to identify and categorise nutritional deficiency syndrome in citrus leaves using image processing and machine learning. The method includes ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

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 ...
Open Heart

Long-term prognostic impact of in-hospital serum albumin concentration changes in patients hospitalised for heart failure

Background Malnutrition influences prognosis in patients with heart failure, but current nutritional evaluation methods are ...
IEEE

Enhancing Prediction Accuracy Through Random Forest in Classification and Regression

Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.