I am an assistant professor at the Julius Center of the University Medical Center Utrecht. I conducted my PhD research at the LIIR Research Lab of the Computer Science Department, KU Leuven.

My main research focus is on clinical natural language processing, prediction modeling, and machine learning in medicine. I am very interested in how to effectively use routine care data to arrive at a better prognosis for patients.

If you wish to do a thesis or internship in this area, feel free to send me an email (aleeuw15 [at] umcutrecht [dot] nl), or have a look at Konjoin!

News

• [November, 2024] Yu-Wen Chen started her PhD! She will work on the methodology of evaluating large language models in healthcare!

• [September, 2024] Great to be able to contribute to the first evaluation of the GPT-based application to make draft discharge summaries developed by UMCU Digital Health (read more…)

• [June, 2024] Happy that our perspective with Anne de Hond on evaluation of LLMs for clinical care applications was published at the Lancet Digital Health!

• [June, 2024] Great to see Isa Spiero presenting her work with Matthew Scheeres on comparing language models to extract signs and symptoms from Dutch GP notes at the Dutch Clinical NLP Workshop!

• [January, 2024] Happy that our article, a result from great collaboration with Madhumita Sushil, on the downstream impact of using NLP in medical association studies on the actual study results was published in the Journal of Clinical Epidemiology!

• [January, 2024] Happy that our article, the result of the thesis project of Zwierd Grotenhuis, on the use of text mining for extraction of health outcomes for prognostic model development was published in Computers in Biology and Medicine!

• [December, 2023] The article by Merijn Rijk on the recording of signs, symptoms and measurements in free text fields of primary care electronic health records was accepted at Journal of Clinical Epidemiology!

• [Sept, 2023] Happy that Isa Spiero’s article on comparing supervised and semi-supervised machine learning approaches in NTCP modeling to predict complications in head and neck cancer patients was published at Clinical and Translational Radiation Oncology!

• [Sept, 2023] Our paper on trends in population characteristics and the performance of the EuroSCORE II over time was published at the European Journal of Cardio-Thoracic Surgery.

• [Aug, 2023] Lotta Meijerink started her PhD! She will work on the methodology of developing, evaluating, monitoring, and updating of AI-based clinical prediction models.

• [Feb, 2023] The RAISE: Responsible AI Science Explorations project has started! On the new wiki you can find the the information on our subproject on error propagation and statistical validity of clinical text mining in medical prediction research.

• [Jan, 2023] Together with dr. Madhumita Sushil we are conducting a follow up study on our N2C2 submission about extraction of social factors from clinical reports. We investigated the impact of using different textual extraction models on the results of a downstream medical association study, and released a preprint on the results so far.

• [Dec, 2022] Our article on the relation between prediction model performance measures and patient selection outcomes for proton therapy in head and neck cancer, has been published in Radiotherapy and Oncology. Code can be found here.

• [Dec, 2022] Together with dr. Ewoud Schuit, we received ZonMw funding for the project “WhyMBA: Why and when to use the Model-Based Approach to evaluate clinical effects of radiotherapy techniques?”, to investigate the conditions for proper use of the model-based clinical evaluation approach for the evaluation of new radiotherapy techniques.

• [Dec, 2022] Isa Spiero started her PhD! She will look at the use of natural language processing in medical research: in systematic reviews and prediction studies.

• [Aug, 2022] Happy to announce that our project “RAISE: Responsible AI Science Explorations” was funded by an NWA small projects grant, in which I will lead a methodological subproject investigating error propagation and statistical validity of clinical text mining in medical prediction research via simulation studies!

• [July, 2022] Together with dr. Madhumita Sushil (UCSF) we participated in the N2C2 challenge on extraction of social determinants of health from clinical records! (code and abstract can be found here)

• [Jan, 2022] Our study about collinearity in clinical prediction modelling has been published in Diagnostic and Prognostic Research (corresponding code can be found here).

• [Jan, 2022] Our scoping review about guidelines for AI-based medical prediction models was published at npj Digital Medicine.