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Publicaties

Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study

Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study.

How Does Routine Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography Modify the Current Management of Prostate Cancer?: A Multidisciplinary View

Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI

The Conundrum of Treating de novo metastatic Hormone-Sensitive Prostate Cancer

The DRAGON benchmark for clinical NLP

The scientific evidence of commercial AI products for MRI acceleration: a systematic review

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

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

Pers/media

Collega's in de media

Lek in de pijpleiding

Pilot 'AI in radiology training' resounding success

Consortium ROBUST receives NWO funding for research into reliable AI

1,9 miljoen euro subsidie voor terugdringen van scantijd MRI bij prostaatkanker

Subsidie voor onderzoek naar snellere MRI-scan met AI

1,9 miljoen euro subsidie voor snellere MRI-scan met artificial intelligence

Subsidie voor onderzoek naar het verkorten van de duur van MRI-scans

Bijna 2 miljoen euro subsidie voor snellere MRI-scan met artificial intelligence