Zobrazeno 1 - 10
of 4 026
pro vyhledávání: '"Lee Simon"'
Autor:
Ono, Kyoka, Lee, Simon A.
Recent research has explored how Language Models (LMs) can be used for feature representation and prediction in tabular machine learning tasks. This involves employing text serialization and supervised fine-tuning (SFT) techniques. Despite the simpli
Externí odkaz:
http://arxiv.org/abs/2406.13846
Autor:
Lee, Simon, Einecke, Sabrina, Rowell, Gavin, Balazs, Csaba, Bellido, Jose A., Dai, Shi, Filipović, Miroslav, Harvey, Violet M., McGee, Padric, Marinos, Peter, Tothill, Nicholas, White, Martin
As TeV gamma-ray astronomy progresses into the era of the Cherenkov Telescope Array (CTA), instantaneously following up on gamma-ray transients is becoming more important than ever. To this end, a worldwide network of Imaging Atmospheric Cherenkov Te
Externí odkaz:
http://arxiv.org/abs/2406.08807
Enhancing Antibiotic Stewardship using a Natural Language Approach for Better Feature Representation
The rapid emergence of antibiotic-resistant bacteria is recognized as a global healthcare crisis, undermining the efficacy of life-saving antibiotics. This crisis is driven by the improper and overuse of antibiotics, which escalates bacterial resista
Externí odkaz:
http://arxiv.org/abs/2405.20419
Autor:
Lee, Simon A., Lindsey, Timothy
Large Language Models (LLMs) have become a pivotal research area, potentially making beneficial contributions in fields like healthcare where they can streamline automated billing and decision support. However, the frequent use of specialized coded l
Externí odkaz:
http://arxiv.org/abs/2403.10822
Autor:
Nicolai Franzmeier, Julia Hartmann, Alexander N. W. Taylor, Miguel Á. Araque-Caballero, Lee Simon-Vermot, Lana Kambeitz-Ilankovic, Katharina Bürger, Cihan Catak, Daniel Janowitz, Claudia Müller, Birgit Ertl-Wagner, Robert Stahl, Martin Dichgans, Marco Duering, Michael Ewers
Publikováno v:
Alzheimer’s Research & Therapy, Vol 10, Iss 1, Pp 1-12 (2018)
Abstract Background Recent evidence derived from functional magnetic resonance imaging (fMRI) studies suggests that functional hubs (i.e., highly connected brain regions) are important for mental health. We found recently that global connectivity of
Externí odkaz:
https://doaj.org/article/7ec3296c9d4647579eebcabe60f5f089
Autor:
Lee, Simon A., Jain, Sujay, Chen, Alex, Ono, Kyoka, Fang, Jennifer, Rudas, Akos, Chiang, Jeffrey N.
In this work, we introduce the Multiple Embedding Model for EHR (MEME), an approach that serializes multimodal EHR tabular data into text using pseudo-notes, mimicking clinical text generation. This conversion not only preserves better representation
Externí odkaz:
http://arxiv.org/abs/2402.00160
Autor:
Lee Simon-Vermot, Alexander N. W. Taylor, Miguel À. Araque Caballero, Nicolai Franzmeier, Katharina Buerger, Cihan Catak, Daniel Janowitz, Lana M. Kambeitz-Ilankovic, Birgit Ertl-Wagner, Marco Duering, Michael Ewers
Publikováno v:
Frontiers in Aging Neuroscience, Vol 10 (2018)
Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and
Externí odkaz:
https://doaj.org/article/82ed337cb6b247ca8d029216378f81d6