Devdiscourse

Data-driven AI approach narrows diagnostic gap between dengue and chikungunya

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
GitHub

o-ronin-o/decision-trees-random-forest_from_scratch_probabilistic-classifier

Here's the complete project structure: decision-trees-random-forest_from_scratch_probabilistic-classifier/ │ ├── data/ │ ├── raw ...
GitHub

Soft Decision Tree classifier: explainable and extendable PyTorch implementation

[Click here for an explanation regarding the code and how to start: https://github.com/KI-Research-Institute/Soft-Decision-Tree/blob/main/Instructions] Background and ...
IPM

Prescribed burning helps store forest carbon in big, fire-resistant trees

After more than a century of fire suppression in California’s forests, mounting evidence shows that frequent fire — through practices like prescribed fire or Indigenous cultural burning — can improve ...
Frontiers

Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
IEEE

Improved Accuracy in Detection of Driver Drowsiness Using Novel Random Forest Classifier Compared with Decision Tree Classifier

Abstract: The goal of this study is to evaluate how well driver drowsiness can be detected using two different machine learning methods: the Decision Tree Classifier and the Novel Random Forest ...
IEEE

Leaf–Wood Separation in Tree Point Clouds via Unlearning-Driven Supervoxel Random Forest

Abstract: Accurate separation of wood and leaf components from tree point clouds is essential for precise tree parameter estimation and high-fidelity 3-D model reconstruction. However, deep learning ...