- home
- Advanced Search
2 Research products, page 1 of 1
Loading
- Research software . 2022Open AccessAuthors:Leaman, Robert;Leaman, Robert;Publisher: Zenodo
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. However, identifying scientific articles relevant to Long Covid is challenging since there is no standardized or consensus terminology. We developed an iterative human-in-the-loop machine learning framework combining data programming with active learning into a robust ensemble model, demonstrating higher specificity and considerably higher sensitivity than other methods. This dataset contains the source code (python and shell scripts) used to create the Long Covid collection, along with a snapshot of processed data and predictions. This research was supported by the Intramural Research Program of the National Library of Medicine, National Institutes of Health.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research software . 2022Open AccessAuthors:White, Luke A.; Maxey, Benjamin S.; Solitro, Giovanni F.; Takei, Hidehiro; Conrad, Steven A.; Alexander, J. Steven;White, Luke A.; Maxey, Benjamin S.; Solitro, Giovanni F.; Takei, Hidehiro; Conrad, Steven A.; Alexander, J. Steven;Publisher: figshare
Additional file 13. Combine Pressures Python Script. Custom Python script used to combine pressure waveforms recorded from pressure sensors placed at the inspiratory and expiratory limbs during FALCON ventilation.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
2 Research products, page 1 of 1
Loading
- Research software . 2022Open AccessAuthors:Leaman, Robert;Leaman, Robert;Publisher: Zenodo
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. However, identifying scientific articles relevant to Long Covid is challenging since there is no standardized or consensus terminology. We developed an iterative human-in-the-loop machine learning framework combining data programming with active learning into a robust ensemble model, demonstrating higher specificity and considerably higher sensitivity than other methods. This dataset contains the source code (python and shell scripts) used to create the Long Covid collection, along with a snapshot of processed data and predictions. This research was supported by the Intramural Research Program of the National Library of Medicine, National Institutes of Health.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research software . 2022Open AccessAuthors:White, Luke A.; Maxey, Benjamin S.; Solitro, Giovanni F.; Takei, Hidehiro; Conrad, Steven A.; Alexander, J. Steven;White, Luke A.; Maxey, Benjamin S.; Solitro, Giovanni F.; Takei, Hidehiro; Conrad, Steven A.; Alexander, J. Steven;Publisher: figshare
Additional file 13. Combine Pressures Python Script. Custom Python script used to combine pressure waveforms recorded from pressure sensors placed at the inspiratory and expiratory limbs during FALCON ventilation.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.