The added value of text from Dutch general practitioner notes in predictive modeling
Objective: This work aims to explore the value of Dutch unstructured data, in combination with structured data, for the development of prognostic prediction models in a general practitioner (GP) setting. Materials and methods: We trained and validated prediction models for 4 common clinical prediction problems using various sparse text representations, common prediction algorithms, and observational GP electronic health record (EHR) data. We trained and validated 84 models internally and externally on data from different EHR systems. Results: On average, over all the different text representat... Mehr ...
Verfasser: | |
---|---|
Dokumenttyp: | other |
Erscheinungsdatum: | 2023 |
Verlag/Hrsg.: |
Zenodo
|
Schlagwörter: | clinical prediction model / electronic health records / machine learning / natural language processing / prognostic prediction |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28639743 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.1093/jamia/ocad160 |