IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
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 ...
IEEE

Federated Function-on-function Regression with an Efficient Gradient Boosting Algorithm for Privacy-Preserving Telemedicine

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...