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Titlebook: Non-Local Cell Adhesion Models; Symmetries and Bifur Andreas Buttensch?n,Thomas Hillen Book 2021 The Editor(s) (if applicable) and The Auth

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11#
發(fā)表于 2025-3-23 11:29:49 | 只看該作者
Discussion and Future DirectionsThe central building block to include adhesive interactions between cells in reaction-advection-diffusion models of tissues is to use a non-local term.
12#
發(fā)表于 2025-3-23 17:17:48 | 只看該作者
Andreas Buttensch?n,Thomas Hillenterfaced with the international nomenclature LOINC, and developed in collaboration with experts from all biological disciplines. Our goal is to establish a platform for publishing and maintaining the AP-HP laboratory data dictionary, which can satisfy both the requirements concerning the controlled
13#
發(fā)表于 2025-3-23 20:14:49 | 只看該作者
14#
發(fā)表于 2025-3-24 00:25:09 | 只看該作者
Natural Language Processing algorithms (NLP). Within the framework of the PSIP project, the French Multi- Terminology Indexer (FMTI) is used to extract drug-related information from records for the detection of Adverse Drug Events (ADEs) that can endanger the patients. FMTI is here needed in the ab
15#
發(fā)表于 2025-3-24 03:21:47 | 只看該作者
16#
發(fā)表于 2025-3-24 08:55:12 | 只看該作者
17#
發(fā)表于 2025-3-24 14:24:19 | 只看該作者
18#
發(fā)表于 2025-3-24 14:51:52 | 只看該作者
Andreas Buttensch?n,Thomas Hillenshots. Based on a list of rules and a repository of stays, it allows for displaying the important rules, the related statistics, and the complete information about the suspicious cases. The knowledge is contextualized, i.e. it depends on the medical department. The tool is deployed in a French hospi
19#
發(fā)表于 2025-3-24 21:54:30 | 只看該作者
gorithm and the other using the phonemization algorithm. Results: The FMTI tool performs better results using the phonemization algorithm: 97% for precision and 95% for recall. Conclusion: For the PSIP project, we showed that the semantic mining using FMTI can help to extract drug- related informati
20#
發(fā)表于 2025-3-24 23:30:15 | 只看該作者
Andreas Buttensch?n,Thomas Hillengorithm and the other using the phonemization algorithm. Results: The FMTI tool performs better results using the phonemization algorithm: 97% for precision and 95% for recall. Conclusion: For the PSIP project, we showed that the semantic mining using FMTI can help to extract drug- related informati
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