Výsledky vyhledávání - "BJELOGRLIC, Mina"

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ProtoS-ViT: Visual foundation models for sparse self-explainable classifications

Autor: Turbé, Hugues, Bjelogrlic, Mina, Mengaldo, Gianmarco, Lovis, Christian

Prototypical networks aim to build intrinsically explainable models based on the linear summation of concepts. However, important challenges remain in the transparency, compactness, and meaningfulness of the explanations provided by these models. Thi

Externí odkaz: http://arxiv.org/abs/2406.10025

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Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices

Autor: Zaghir, Jamil, Naguib, Marco, Bjelogrlic, Mina, Névéol, Aurélie, Tannier, Xavier, Lovis, Christian

Prompt engineering is crucial for harnessing the potential of large language models (LLMs), especially in the medical domain where specialized terminology and phrasing is used. However, the efficacy of prompt engineering in the medical domain remains

Externí odkaz: http://arxiv.org/abs/2405.01249

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Akademický článek

Use of the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for Processing Free Text in Health Care: Systematic Scoping Review

Autor: Gaudet-Blavignac, Christophe, Foufi, Vasiliki, Bjelogrlic, Mina, Lovis, Christian

Publikováno v: Journal of Medical Internet Research, Vol 23, Iss 1, p e24594 (2021)

BackgroundInteroperability and secondary use of data is a challenge in health care. Specifically, the reuse of clinical free text remains an unresolved problem. The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) has become the unive

Externí odkaz: https://doaj.org/article/5a25186f9868455296e712d2b7014bd6

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FRASIMED: a Clinical French Annotated Resource Produced through Crosslingual BERT-Based Annotation Projection

Autor: Zaghir, Jamil, Bjelogrlic, Mina, Goldman, Jean-Philippe, Aananou, Soukaïna, Gaudet-Blavignac, Christophe, Lovis, Christian

Natural language processing (NLP) applications such as named entity recognition (NER) for low-resource corpora do not benefit from recent advances in the development of large language models (LLMs) where there is still a need for larger annotated dat

Externí odkaz: http://arxiv.org/abs/2309.10770

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Evaluation of post-hoc interpretability methods in time-series classification

Autor: Turbé, Hugues, Bjelogrlic, Mina, Lovis, Christian, Mengaldo, Gianmarco

Publikováno v: Turb\'e H, Bjelogrlic M, Lovis C, Mengaldo G. Evaluation of post-hoc interpretability methods in time-series classification. Nature Machine Intelligence. 2023 Mar;5(3):250-60

Post-hoc interpretability methods are critical tools to explain neural-network results. Several post-hoc methods have emerged in recent years, but when applied to a given task, they produce different results, raising the question of which method is t

Externí odkaz: http://arxiv.org/abs/2202.05656

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