| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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He, Huan
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (11/11 displayed)
- 2023An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)citations
- 2023DEM multi-scale insights on the pre-failure behavior of mature structured sandscitations
- 2022DEM analysis of small and small-to-medium strain shear modulus of sandscitations
- 2022Micromechanical insights on the stiffness of sands through grain-scale tests and DEM analyses
- 2016Influence of a bioadmixture on standardized parameters of cementitious materials
- 2016SHAPE ANALYSIS OF FINE AGGREGATES USED FOR CONCRETE ; Analyse morphologique d'agrégats fins utilisés dans le bétoncitations
- 2015Cement paste surface roughness analysis using Coherence Scanning Interferometry and Confocal Microscopycitations
- 2012Workability tests on fresh concrete formulated with eco-friendly admixture
- 2012Influence of Particle Packing on Elastic Properties of Concretecitations
- 2012Effet de l'empilement et de la forme des additions dans les propriétés des liants à matrice cimentaire
- 2011Influence of Particle Packing on Fracture Properties of Concretecitations
Places of action
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article
An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C)
Abstract
<jats:title>Abstract</jats:title><jats:p>Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.</jats:p>