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ShareScore release 0.9.0
Dataset results
5 results for “research data, data discovery”
Complete supplementary data related to palynological research of International Ocean Discovery Program (IODP) Expedition 364
<p>Supplemental data relating to Vann Smith's 2020 dissertation at Louisiana State University</p>
Data from: Trends in anesthesiology research: a machine learning approach to theme discovery and summarization
Objectives: Traditionally, summarization of research themes and trends within a given discipline was accomplished by manual review of scientific works in the field. However, with the ushering in of the age of "big data", new methods for discovery of such information become necessary as traditional techniques become increasingly difficult to apply due to the exponential growth of document repositories. Our objectives are to develop a pipeline for unsupervised theme extraction and summarization of thematic trends in document repositories, and to test it by applying it to a specific domain. Methods: To that end, we detail a pipeline, which utilizes machine learning and natural language processing for unsupervised theme extraction, and a novel method for summarization of thematic trends, and network mapping for visualization of thematic relations. We then apply this pipeline to a collection of anesthesiology abstracts. Results: We demonstrate how this pipeline enables discovery of major themes and temporal trends in anesthesiology research and facilitates document classification and corpus exploration. Discussion: The relation of prevalent topics and extracted trends to recent events in both anesthesiology, and healthcare in general, demonstrates the pipeline's utility. Furthermore, the agreement between the unsupervised thematic grouping and human-assigned classification validates the pipeline's accuracy and demonstrates another potential use. Conclusion: The described pipeline enables summarization and exploration of large document repositories, facilitates classification, aids in trend identification. A more robust and user-friendly interface will facilitate the expansion of this methodology to other domains. This will be the focus of future work for our group.
Data from: Trends in anesthesiology research: a machine learning approach to theme discovery and summarization
Open the record for dataset details and reuse information.
Characteristics and Treatment Patterns of Patients With Sickle Cell Disease in Globin Research Network for Data and Discovery Registry
ClinicalTrials.gov study NCT06662812. IPD Sharing: Not stated. Countries: 1. Publications: 0.
LC-MS raw data for "A new generation of nanobody research tools using improved mass spectrometry-based discovery methods"
<p>This dataset contains LC-MS raw data for VHH identifications from the project "A new generation of nanobody research tools using improved mass spectrometry-based discovery methods." The descriptions of the raw data files are in Summary_Table_MS_RawData.pdf. Files are in the format of Thermo RAW in zip archives.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.