activity
20242026
most citedA Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Translation as a Computationally Efficient Bridge: Feasibility of English BERT for Low-Resource Languages

Hielke Muizelaar, Giulia Rivetti, Marco Spruit +1

BERT models have revolutionised Natural Language Processing (NLP) through their ability to process unstructured text across diverse domains. However, developing high-quality BERT m…

cs.IR2026

OpenExtract: Automated Data Extraction for Systematic Reviews in Health

Jim Achterberg, Bram Van Dijk, Jing Meng +8

This study presents OpenExtract, an open-source pipeline for automated data extraction in large-scale systematic literature reviews. The pipeline queries large language models (LLM…

cs.LG2026

XGenBoost: Synthesizing Small and Large Tabular Datasets with XGBoost

Jim Achterberg, Marcel Haas, Bram van Dijk +1

Tree ensembles such as XGBoost are often preferred for discriminative tasks in mixed-type tabular data, due to their inductive biases, minimal hyperparameter tuning, and training e…

cs.DB2025

The Data Sharing Paradox of Synthetic Data in Healthcare

Jim Achterberg, Bram van Dijk, Saif ul Islam +6

Synthetic data offers a promising solution to privacy concerns in healthcare by generating useful datasets in a privacy-aware manner. However, although synthetic data is typically…

cs.CY2024★ 1 cited

A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications

Bram van Dijk, Saif ul Islam, Jim Achterberg +6

Data-driven technologies have improved the efficiency, reliability and effectiveness of healthcare services, but come with an increasing demand for data, which is challenging due t…