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Over ons Praktische zaken Waar vindt u ons dr. M.S. (Matthijs) Berends

Research interests

Dr. Matthijs S. Berends works as a medical epidemiologist/microbiologist the University Medical Center Groningen (UMCG) and Certe Foundation. He is an expert on microbial epidemiology and data science. With a background in Medical Biology, Medical Microbiology and Clinical Epidemiology, he wrote his PhD thesis “A New Instrument for Microbial Epidemiology” (DOI 10.33612/diss.177417131) on the development of a novel method for antimicrobial resistance (AMR) data analysis. This publicly available method is being used in 175 countries and was downloaded over 85,000 times. For this achievement, the University of Groningen rewarded him with the Open Research Award in 2021. The preprint about the method was in the ResearchGate top 10 weekly most read preprints ever and is according to Altmetrics in the 97th percentile of most popular research ever measured. It was published in the Journal of Statistical Software (IF 22.1).

Dr. Berends’ research focusses on the possibilities and effects to work with microbiological data in novel ways, especially with regard to AMR, by using predictive modelling and machine learning. Additionally, for his current postdoc position at UMCG department of Primary Care Medicine, he develops machine learning models to predict acute and long COVID in primary care patients.

Google Scholar: https://scholar.google.com/citations?hl=en&user=sAoHvIgAAAAJ

 

Publicaties

A New Instrument for Microbial Epidemiology: Empowering Antimicrobial Resistance Data Analysis

Impact of COVID-19 on Dutch general practitioner prenatal healthcare: an interrupted time-series approach

Uncovering the spread of drug-resistant bacteria through next-generation sequencing based surveillance: transmission of extended-spectrum β-lactamase-producing Enterobacterales by a contaminated duodenoscope

A Natural Language Processing Model for COVID-19 Detection Based on Dutch General Practice Electronic Health Records by Using Bidirectional Encoder Representations From Transformers: Development and Validation Study

Better antimicrobial resistance data analysis and reporting in less time

Comparison of methods to identify and characterize Post-COVID syndrome using electronic health records and questionnaires

Dutch GP healthcare consumption in COVID-19 heterogeneous regions: an interregional time-series approach in 2020-2021

Impact of reduced antibiotic treatment duration on antimicrobial resistance in critically ill patients in the randomized controlled SAPS-trial

Surface water in Lower Saxony: A reservoir for multidrug-resistant Enterobacterales

Vancomycin-resistant enterococci (VRE) in hospital settings across European borders: a scoping review comparing the epidemiology in the Netherlands and Germany

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