Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Matias Nicolas Bossa"'
Publikováno v:
IEEE Access, Vol 12, Pp 10120-10134 (2024)
Large language models provide high-accuracy solutions in many natural language processing tasks. In particular, they are used as word embeddings in sentiment analysis models. However, these models pick up on and amplify biases and social stereotypes
Externí odkaz:
https://doaj.org/article/0bf6b4166d434aabb73d28394f148412
Publikováno v:
Informatik aktuell ISBN: 9783658369316
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a2541620e1a25f56df757fe82ce8611
http://orbilu.uni.lu/handle/10993/51681
http://orbilu.uni.lu/handle/10993/51681
Publikováno v:
Frontiers in Aging Neuroscience, Vol 16 (2024)
IntroductionStudying the spatiotemporal patterns of amyloid accumulation in the brain over time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography (PET) imaging plays a pivotal role because it allows for the visualizat
Externí odkaz:
https://doaj.org/article/78867da5432a4eb19a1b055708a008fe
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0302197 (2024)
Our study aims to investigate the interdependence between international stock markets and sentiments from financial news in stock forecasting. We adopt the Temporal Fusion Transformers (TFT) to incorporate intra and inter-market correlations and the
Externí odkaz:
https://doaj.org/article/1264c279b06e42d895add8d8acd7cd5d
Autor:
Matías Nicolás Bossa, Hichem Sahli
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract Data-driven Alzheimer’s disease (AD) progression models are useful for clinical prediction, disease mechanism understanding, and clinical trial design. Most dynamic models were inspired by the amyloid cascade hypothesis and described AD pr
Externí odkaz:
https://doaj.org/article/79efaee01d934fcebea42f9a1ebbdd92