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Over ons Praktische zaken Waar vindt u ons prof. dr. ir. P.M.A. (Peter) van Ooijen

Publicaties

A comparative study of federated learning methods for COVID-19 detection

A framework to integrate artificial intelligence training into radiology residency programs: preparing the future radiologist

Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer

Explainable machine learning model based on clinical factors for predicting the disappearance of indeterminate pulmonary nodules

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability

Classification of Movement Disorders Using Video Recordings of Gait with Attention-based Graph Convolutional Networks

Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer

CT-based deep multi-label learning prediction model for outcome in patients with oropharyngeal squamous cell carcinoma

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images

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Pers/media

Terugblik Winterschool: ‘Een rijbewijs voor kunstmatige intelligentie en gezondheid’

Kunstmatige intelligentie helpt UMCG bij opsporen ziektes

Hoe kan kunstmatige intelligentie helpen om longkanker eerder op te sporen?

Hoe kan kunstmatige intelligentie helpen om longkanker eerder op te sporen?

Data Science Center in Health (DASH)

DAME: Deep learning Algorithms for Medical image Evaluation

DAME project

Data control with AI: who’s in charge?

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