Zobrazeno 1 - 10
of 154
pro vyhledávání: '"Teodoro, Douglas"'
The Medical Subject Headings (MeSH), one of the main knowledge organization systems in the biomedical domain, is constantly evolving following the latest scientific discoveries in health and life sciences. Previous research focused on quantifying inf
Externí odkaz:
http://arxiv.org/abs/2406.18792
Autor:
Yazdani, Anthony, Bornet, Alban, Khlebnikov, Philipp, Zhang, Boya, Rouhizadeh, Hossein, Amini, Poorya, Teodoro, Douglas
Adverse drug events (ADEs) significantly impact clinical research, causing many clinical trial failures. ADE prediction is key for developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for
Externí odkaz:
http://arxiv.org/abs/2404.12827
This paper outlines the performance evaluation of a system for adverse drug event normalization, developed by the Data Science for Digital Health (DS4DH) group for the Social Media Mining for Health Applications (SMM4H) 2023 shared task 5. Shared tas
Externí odkaz:
http://arxiv.org/abs/2308.12877
Current approaches for clinical information extraction are inefficient in terms of computational costs and memory consumption, hindering their application to process large-scale electronic health records (EHRs). We propose an efficient end-to-end mod
Externí odkaz:
http://arxiv.org/abs/2302.04185
This paper describes the work of the Data Science for Digital Health (DS4DH) group at the TREC Health Misinformation Track 2021. The TREC Health Misinformation track focused on the development of retrieval methods that provide relevant, correct and c
Externí odkaz:
http://arxiv.org/abs/2202.06771
Autor:
Ehrler, Frederic, Wipfli, Rolf, Teodoro, Douglas, Sarrey, Everlyne, Walesa, Magali, Lovis, Christian
Publikováno v:
JMIR mHealth and uHealth, Vol 1, Iss 1, p e7 (2013)
BackgroundWorking in a clinical environment requires unfettered mobility. This is especially true for nurses who are always on the move providing patients’ care in different locations. Since the introduction of clinical information systems in hospi
Externí odkaz:
https://doaj.org/article/5efb71b3ea7546fc9beb9ab7849401d5
We consider the hierarchical representation of documents as graphs and use geometric deep learning to classify them into different categories. While graph neural networks can efficiently handle the variable structure of hierarchical documents using t
Externí odkaz:
http://arxiv.org/abs/2110.15710
Autor:
Teodoro, Douglas, Pasche, Emilie, Gobeill, Julien, Emonet, Stéphane, Ruch, Patrick, Lovis, Christian
Publikováno v:
Journal of Medical Internet Research, Vol 14, Iss 3, p e73 (2012)
BackgroundAntimicrobial resistance has reached globally alarming levels and is becoming a major public health threat. Lack of efficacious antimicrobial resistance surveillance systems was identified as one of the causes of increasing resistance, due
Externí odkaz:
https://doaj.org/article/e5792d809e9d4d9a9594bdfc25fa65c2
Autor:
Shiri, Isaac, Razeghi, Behrooz, Ferdowsi, Sohrab, Salimi, Yazdan, Gündüz, Deniz, Teodoro, Douglas, Voloshynovskiy, Slava, Zaidi, Habib
Publikováno v:
In Journal of Biomedical Informatics February 2024 150
Chemical patent documents describe a broad range of applications holding key reaction and compound information, such as chemical structure, reaction formulas, and molecular properties. These informational entities should be first identified in text p
Externí odkaz:
http://arxiv.org/abs/2007.12569