Hi! I'm Thomas

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  • Name : Thomas Debray
  • Freelance : Available
  • Age : 34
  • Email : contact
  • Phone :
  • Address : Utrecht, the Netherlands
  • Nationality : Belgium
  • Gender : Male
  • Marital Status :
  • Work Status : Assistant Professor

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Qualifications

  • PhD, Epidemiology. Utrecht University (2013), Utrecht, The Netherlands
  • MSc, Clinical Epidemiology. Utrecht University (2013), Utrecht, The Netherlands
  • MSc, Artificial Intelligence. Maastricht University (2009), Maastricht, The Netherlands
  • BSc, Applied Computer Science. University College Ghent (2007), Ghent, Belgium

Supervision

Steven Nijman.

PhD Thesis. .
Utrecht University, Oct 2018 - present

Jeroen Hoogland.

PhD Thesis. .
Utrecht University, Feb 2018 - present

Huong Ly Le.

PhD Thesis. .
Utrecht University, Dec 2016 - Dec 2017

Valentijn de Jong.

PhD Thesis. .
Utrecht University, Jul 2016 - present

Marieke van Rijn.

PhD Thesis. Predicting Progression in Chronic Kidney Disease.
Radboud University Nijmegen, Feb 2016 - present

Johanna Damen.

PhD Thesis. Systematic reviews and meta-analyses of prediction model studies: methods and applications.
Utrecht University, Jan 2014 - Jun 2018

Laura Hofstee.

MSc Thesis. Predicting the Individualized Risk of Arrhythmogenic Cardiomyopathy: Adoption of Machine Learning Techniques Combining Patients' Data with ECG Information.
Utrecht University, Sep 2019 - present

Rutger van de Leur.

MSc Thesis. Two-step determination of optimal settings for preventing arcing with an irreversible electroporation cardiac ablation device for atrial fibrillation.
Utrecht University, Feb 2018 - present

Amélie Rolle.

MSc Thesis. Early Identification of sickle-cell disease patients at risk for complicated outcomes in intensive care unit.
Université de Montpellier, Jan 2018 - Jun 2018

Leandro Cortellini.

MSc Thesis. Overview of prognostic model research and validation studies that use registry data.
Utrecht University, Sep 2017 - Mar 2018

Rogier van der Sluijs.

MSc Thesis. Prehospital Trauma Triage: Predicting Injury Severity.
Utrecht University, Jan 2017 - Jan 2019

Rogier van der Sluijs.

Internship. Modeling vital signs in prediction research.
Utrecht University, Jan 2017 - Feb 2017

Thesis examination

  • PhD Thesis. Todd Bradley Smith (10 Oct 2019). Population based risk stratification for colorectal cancer. School of Public Health. Imperial College London. United Kingdom.
  • PhD Thesis. Miriam Hattle (8 Jul 2019). Development and application of multivariate meta-analysis in medical research: borrowing strength across multiple correlated outcomes. Department of Primary Care & Health Sciences. Keele University. United Kingdom.
  • PhD Thesis. Glen Martin (2 Oct 2017). Methodology in Developing Clinical Prediction Models within Defined Populations: applications in transcatheter aortic valve implantation and an analysis of the British Cardiovascular Interventional Society national registry. Division of Informatics, Imaging and Data Science. School of Health Sciences. University of Manchester. United Kingdom.
  • PhD Thesis. Laure Wynants (1 Dec 2016). Clinical Risk Prediction Models based on Multicenter Data: Methods for Model Development and Validation. Faculty of Engineering Science. University of Leuven. Belgium.

International Activities

Project Lead

In collaboration with the ZIKV IPD Consortium, investigators at Utrecht University will lead the development of the detailed analysis plan and draft code to conduct the ZIKV IPD meta-analysis.

Project details...

This project aims to develop innovative approaches to the synthesis and analysis of clinical-epidemiological (CE) and high dimensional laboratory (HDL) data, and modify governance models for cloud-based repositories elaborated by and for scientists in high-income countries to meet the specific challenges of synthesizing CE and HDL data and sharing data across international cohorts and with the Open Science community.

Project details...

This project aims to develop a statistical framework that utilizes big datasets to identify and account for heterogeneity in predictor effects. Hereto, existing meta-analysis methods will be improved upon and a new penalization algorithm will be derived to enhance the estimation and inclusion of relevant predictors during the adaptation and development of prediction models. Ultimately, this will reduce the need for further validation and adaptation of prediction models.

Project details...