CV

Education

• 2017 - 2021: MSc in Epidemiology, Utrecht University
  • Specialization: Medical Statistics and Cardiovascular Epidemiology
  • Electives:
    • Introduction to Data Science Summer School at the London School of Economics
    • Deep Learning at the University of Amsterdam
  • GPA 4.0 / Average grade 8.4
• 2012 - 2020: BSc & MSc in Medicine, Utrecht University
  • Participated in Medical Master Honours Program
  • Elective internships:
    • 2019 - 2020: Specialization year Vital Functions with focus on Cardiology (UMC Utrecht), Anesthesiology (Diakonessenhuis Utrecht) and Intensive Care Medicine (St. Antonius Nieuwegein)
    • 2019: Emergency Medicine internship at the Emergency Department of the Academisch Ziekenhuis Paramaribo, Suriname
    • 2017: Ophthalmology internship at Pacific Eye Institute, Los Angeles, USA & Eye Center South, Dothan, USA
    • 2016: Obstetrics and Gynaecology internship at Groote Schuur Hospital and Mowbray Maternity Clinic, Cape Town, South Africa
  • GPA 4.0 / Average grade 8.3
• 2006 - 2012: Pre-university education, Stedelijk Gymnasium Arnhem
  • Subjects: Dutch, English, Spanish, Greek, Physics, Chemistry, Mathematics, Biology and Economy
  • Graduated Cum Laude

Work experience

• 2021 - today: Co-founder, Ocqam Statistics
  • Developing a tool to help other scientists find the statistical analysis they need (https://ocq.am)
• 2018 - today: PhD-student, Department of Cardiology, UMC Utrecht
  • Project: Deep learning for automated analysis of the electrocardiogram and the development of an artificial intelligence-enabled portable multi-lead ECG device
• 2014 - 2020: Teaching assistant, Utrecht University
  • Teaching small groups of Medical students in Anatomy and Epidemiology
• 2015 - 2018: Research assistant, Intensive Care Department, UMC Utrecht
  • Screening patients for several studies and managing large databases
• 2013 - 2018: Ward Assistant, UMC Utrecht
• 2014 - 2017: National Reserve Corps, Royal Netherlands Army

Skills

• Languages:
  • Dutch (C2, mother tongue)
  • English (C1, Cambridge Certificate)
  • Spanish and German (A2)

Interests

Sailing, technology, photography and graphic design

Grants

• 2019: ZonMw/IMDI/DCVA/Dutch Heart Foundation grant “Heart for Sustainable Care” for our consortium

Publications

Delirium in critically ill patients.

Slooter AJC, Van De Leur RR, Zaal IJ. Delirium in critically ill patients. Handb Clin Neurol. 2017;141:449–466.

3D Myocardial Scar Prediction Model Derived from Multimodality Analysis of Electromechanical Mapping and Magnetic Resonance Imaging

Van den Broek HT, Wenker S, van de Leur RR, Doevendans PA, Chamuleau SAJ, van Slochteren FJ, van Es R. 3D Myocardial Scar Prediction Model Derived from Multimodality Analysis of Electromechanical Mapping and Magnetic Resonance Imaging. J Cardiovasc Transl Res. 2019;12:517–527.

Incorporating repeated measurements into prediction models in the critical care setting: A framework, systematic review and meta-analysis

Plate JDJ, Van De Leur RR, Leenen LPH, Hietbrink F, Peelen LM, Eijkemans MJC. Incorporating repeated measurements into prediction models in the critical care setting: A framework, systematic review and meta-analysis. BMC Med Res Methodol. 2019;19.

Automatic Triage of 12‐Lead ECGs Using Deep Convolutional Neural Networks

van de Leur RR, Blom LJ, Gavves E, Hof IE, van der Heijden JF, Clappers NC, Doevendans PA, Hassink RJ, van Es R. Automatic Triage of 12‐Lead ECGs Using Deep Convolutional Neural Networks. J Am Heart Assoc. 2020

fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study

van Montfort SJT, Slooter AJC, Kant IMJ, van de Leur RR, Spies C, de Bresser J, Witkamp TD, Hendrikse J, van Dellen E. fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study. NeuroImage Clin. 2020;27:102347.

Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology

Van de Leur RR^*, Boonstra MJ^*, Bagheri A, Roudijk RW, Sammani A, Taha K, Doevendans PA, Van der Harst P, Van Dam P, Hassink R, Van Es R, Asselbergs FW. Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology. Arrhythmia Electrophysiol Rev. 2020;9(3):146-54.