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Found 10 papers, 1 papers with code
PubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge
PubTator 3. 0 (https://www. ncbi. nlm. nih. gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for key concepts like proteins, genetic variants, diseases, and chemicals.
LitCovid in 2022: an information resource for the COVID-19 literature
LitCovid (https://www. ncbi. nlm. nih. gov/research/coronavirus/), first launched in February 2020, is a first-of-its-kind literature hub for tracking up-to-date published research on COVID-19.
Comprehensively identifying Long Covid articles with human-in-the-loop machine learning
A significant percentage of COVID-19 survivors experience ongoing multisystemic symptoms that often affect daily living, a condition known as Long Covid or post-acute-sequelae of SARS-CoV-2 infection.
Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations
To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature.
LitMC-BERT: transformer-based multi-label classification of biomedical literature with an application on COVID-19 literature curation
However, it has been a primary curation bottleneck due to the nature of the task and the rapid literature growth.
tmVar 3.0: an improved variant concept recognition and normalization tool
We have also processed the entire PubMed and PMC with tmVar3 and released its annotations on our FTP.
Multi-modal, multi-task, multi-attention (M3) deep learning detection of reticular pseudodrusen: towards automated and accessible classification of age-related macular degeneration
The objective was to develop and evaluate the performance of a novel 'M3' deep learning framework on RPD detection.
Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)
The COVID-19 pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread.
Navigating the landscape of COVID-19 research through literature analysis: A bird's eye view
In this study we analyze the LitCovid collection, 13, 369 COVID-19 related articles found in PubMed as of May 15th, 2020 with the purpose of examining the landscape of literature and presenting it in a format that facilitates information navigation and understanding.
Predicting risk of late age-related macular degeneration using deep learning
By 2040, age-related macular degeneration (AMD) will affect approximately 288 million people worldwide.
