Dré Peeters
I'm a PhD candidate in the Diagnostic Image Analysis Group at Radboudumc, Nijmegen. I work on deep learning for lung cancer screening — and on making those models safe enough to trust in the clinic, through uncertainty estimation and out-of-distribution detection.
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AMARA — AI for lung nodule malignancy estimation
My PhD project at Radboudumc: developing and validating a deep learning algorithm for pulmonary nodule malignancy prediction on chest CT, and making it safe for clinical use with uncertainty estimation and out-of-distribution detection.
- Python
- PyTorch
- NumPy
- pandas
- scikit-learn
- Git
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Kilometer tracker
A Django web application for people who share a car: register trips and refuelings per group, see who drove what, and settle fuel expenses fairly.
- Python
- Django
- HTML5
- CSS
- Git
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Automated X-ray quality control
Deep learning models that classify artefacts in phantom images from mammographic devices, supporting the quality control of the Dutch breast cancer screening program at the LRCB.
- Python
- PyTorch
- NumPy
- Git
- 2025
Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules
- 2025
Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge
- 2025
Exploring AI-enabled nodule management for incidentally detected pulmonary nodules on CT