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BSc/MSc Projects

We are continuously looking for interesting new projects. Following the weekly AI for Health meeting there is a consultation hour in which new project proposals can be discussed. To propose a new project, please fill out this form. We ask you to send the completed form to aiforhealth@radboudumc.nl and to make an appointment to discuss the project during one of the consultation hours (every Thursday afternoon 16:00 - 17:00 PM).

Radboud University MSc students are eligible to receive a monthly reimbursement of €500,- for a period of six months. The students are required to present their work in the initial phase and end of the project during the weekly meeting. An overview of current project vacancies can be seen below.

Project Vacancies


Running Projects

Objective home-based bradykinesia assessment in Parkinson’s disease

Development of a model for the automatic identification of Parkinson's disease based on a keyboard test.

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Quantitative facial phenotyping of patients with intellectual disability

Development of a deep learning algorithm for learning face representations.

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A machine learning model to identify neurogenic and infectious fever in ICU patients with acute brain injury

Development of a model that can identify whether a febrile ICU patient with acute brain injury has a neurogenic fever or an infectious fever.

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Muscle and fat segmentation in 3D CT images for body composition assessment

Develop deep learning algorithms for segmentation of muscles and fat tissue in 3D CT images.

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Screening for neuromuscular disorders using automatic classification of muscle ultrasound images

Development of a deep learning algorithm for the automatic classification of muscle ultrasound images.

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Modelling long-term progression of Parkinson’s disease

Development of a model to support treatment decisions regarding cardiovascular risk management in patients with Parkinson’s disease (PD).

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Pneumothorax detection

Development of a system to detect pneumothorax in frontal chest radiographs.

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AI-assisted PD-L1 scoring in lung cancer

Project aimed at development of deep learning algorithms for the (semi-) automated scoring of PD-L1 positive tumor cells, an established biomarker for immunotherapy treatment response in lung cancer patients.

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Predicting changes in quality of life of ICU survivors

Development of a model for prediction of quality of life.

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Automated prenatal ultrasound screening

Project aimed at development of deep learning algorithms for automated detection of twin pregnancies and placenta localization.

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Simulated Prosthetic Hearing in deaf subjects

Development of a neural network based model that improves speech perception in cochlear implant recipients, by optimizing the vocoder strategy in order to restore binaural hearing in deaf subjects.

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Completed Projects

AI steered interventional MRI

Develop Artificial Intelligence (AI) to track tumor targets in interventional MRI.

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Predicting Clinical Deterioration Events

Predicting clinical deterioration events in hospitalized patients by using novel machine learning techniques.

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Text mining pathology reports

Development of a text mining system to accurately make a diagnosis from nephrology pathology reports.

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