A5083800526- Topic Modeling
- Machine Learning in Healthcare
- Biomedical Text Mining and Ontologies
- Misinformation and Its Impacts
- Solid-state spectroscopy and crystallography
- Natural Language Processing Techniques
- Advanced NMR Techniques and Applications
- Peripheral Neuropathies and Disorders
- Genetics, Bioinformatics, and Biomedical Research
- High-pressure geophysics and materials
- Genomics and Phylogenetic Studies
- Ophthalmology and Eye Disorders
- NMR spectroscopy and applications
- Graphite, nuclear technology, radiation studies
- Scientific Computing and Data Management
- Radiomics and Machine Learning in Medical Imaging
- Multiple Sclerosis Research Studies
- COVID-19 Clinical Research Studies
- Superconducting Materials and Applications
Hôpital Européen Georges-Pompidou
2020-2022
Assistance Publique – Hôpitaux de Paris
2017-2022
Centre de Recherche des Cordeliers
2017-2022
Université Paris Cité
2017-2022
Sorbonne Paris Cité
2017-2022
Sorbonne Université
2017-2022
Hôpital Européen
2020-2022
Inserm
2017-2022
Délégation Paris 5
2017
Background A novel disease poses special challenges for informatics solutions. Biomedical relies the most part on structured data, which require a preexisting data or knowledge model; however, diseases do not have models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to model. However, although this idea has often been suggested, no opportunity arisen actually test it in real time. The current coronavirus (COVID-19) pandemic presents such...
The increasing complexity of data streams and computational processes in modern clinical health information systems makes reproducibility challenging. Clinical natural language processing (NLP) pipelines are routinely leveraged for the secondary use data. Workflow management (WMS) have been widely used bioinformatics to handle bottleneck.To evaluate if WMS other practices could impact NLP frameworks.Based on literature across multiple researcho fields (NLP, informatics) we selected articles...
Next-generation sequencing is used on a daily basis to perform molecular analysis determine subtypes of disease (e.g., in cancer) and assist the selection optimal treatment. Clinical bioinformatics handles manipulation data generated by sequencer, from generation interpretation. Reproducibility traceability are crucial issues clinical setting. We have designed an approach based Docker container technology Galaxy, popular support open-source software. Our solution simplifies deployment...
In this study, we extracted information from 6,376 french CT scan semi-structured text reports evaluating the cancer treatment response using RECIST methodology. We evaluated performance against manual annotation of 100 and measured evolution presence over time. The results show high performances extraction as well trends.
<sec> <title>BACKGROUND</title> A novel disease poses special challenges for informatics solutions. Biomedical relies the most part on structured data, which require a preexisting data or knowledge model; however, diseases do not have models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to model. However, although this idea has often been suggested, no opportunity arisen actually test it in real time. The current coronavirus (COVID-19)...