IEEE

Integrating Random Forest With Boundary Enhancement for Mapping Crop Planting Structure at the Parcel Level From Remote Sensing Images

Abstract: Accurately and efficiently obtaining crop planting structure information is critical for precision agriculture. However, the current methods for mapping crop planting structure primarily use ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
GitHub

random-forest-scikit-learn-python-gradio

Machine Learning project to predict water potability using supervised learning algorithms with data preprocessing, model comparison, and deployment using Gradio. Gradio. data preprocessing, model ...
IEEE

AI-Driven Classification of Tsunami-Generating Earthquakes: Harnessing Random Forest, SVM, and Logistic Regression for Early Detection

Abstract: Predicting whether an earthquake will generate a tsunami is critical for early warning systems and disaster mitigation. In this study, we present an AI-driven approach to classify ...
GitHub

Efficient tree-based nonlinear anchor regression and classification for Python.

article{londschien2025, title={Domain Generalization and Adaptation in Intensive Care with Anchor Regression}, author={Londschien, Malte, Burger, Manuel, R{\"a}tsch ...