IEEE

BOTANZ: Improving Agricultural Efficiency Through Random Forest Algorithms

Abstract: By evaluating intricate datasets to maximize plant growth, boost yields, and advance sustainability, smart agriculture—powered by Random Forest machine learning—is transforming botany.
IEEE

Heart Disease Identification Using Machine Learning Algorithm

Abstract: After all advancements in technology and times, prediction and prevention of heart diseases is still a major issue in modern days. Heart diseases play a major role in high death rate in ...
Frontiers

A lightweight cerebrospinal fluid biomarker-based model for first-diagnosis prediction of Parkinson’s disease: model development, external validation, and local deployment

Background: Despite substantial progress in biomarker research, Parkinson’s disease (PD) still lacks widely validated, easily deployable diagnostic tests for reliable early-stage detection, ...
openaccessgovernment

Leveraging machine learning and robust small area estimation methods for stand-level forest inventory

This special report introduces small area estimation (SAE) as a modern approach for producing reliable, stand-level forest inventory information Small area estimation (SAE) is a set of statistical ...