Tom M. SeinenErasmus MC | Erasmus MC · Department of Medical Informatics
Tom M. Seinen
Master of Science
About
6
Publications
616
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41
Citations
Citations since 2017
Introduction
Skills and Expertise
Additional affiliations
January 2019 - May 2019
August 2016 - August 2017
Education
September 2017 - July 2019
September 2015 - August 2017
September 2012 - June 2015
Publications
Publications (6)
Objective:
This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether using text data in addition to more commonly used structured data improves the prediction performance....
Background
We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hosp...
Objectives:
This systematic review aims to provide further insights into the conduct and reporting of clinical prediction model development and validation over time. We focus on assessing the reporting of information necessary to enable external validation by other investigators.
Materials and methods:
We searched Embase, Medline, Web-of-Science...
Objective
This systematic review aims to assess how information from unstructured clinical text is used to develop and validate prognostic risk prediction models. We summarize the prediction problems and methodological landscape and assess whether using unstructured clinical text data in addition to more commonly used structured data improves the p...
Objectives
This systematic review aims to provide further insights into the conduct and reporting of clinical prediction model development and validation over time. We focus on assessing the reporting of information necessary to enable external validation by other investigators.
Materials and Methods
We searched Embase, Medline, Web-of-Science, Coc...
Objective
To develop and externally validate COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission (COVER-H), requiring intensive services (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis.
Methods
We analyzed a federated network of electronic medical records and administrative claim...
