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195
datasets available to search
ShareScore release 0.9.0
Dataset results
195 results for “biomedical”
Biomedical HIV/AIDS Prevention Program Yunnan
ClinicalTrials.gov study NCT03992274. IPD Sharing: NO. Countries: 1. Publications: 0.
How Participants Perceive Biomedical Research in Pulmonology
ClinicalTrials.gov study NCT03397056. IPD Sharing: YES. Countries: 1. Publications: 0.
Clinical Performance of Habitual Wearers of Bioclear 1-day Lenses When Refitted With Biomedics 1-day Extra for 1 Week
ClinicalTrials.gov study NCT02406495. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Clinical Evaluation of Biomedics Monthly Sphere and Avaira Vitality Sphere
ClinicalTrials.gov study NCT06400914. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Development and application of a novel metric to assess effectiveness of biomedical data
Open the record for dataset details and reuse information.
Research Data Management in Health and Biomedical Citizen Science: Practices and Prospects
Open the record for dataset details and reuse information.
sCLIP – An integrated platform to study RNA-protein interactome(s) in biomedical research: identification of CSTF2tau in alternative processing of small nuclear RNAs [CLIP-Seq]
GEO Series GSE92995. Homo sapiens. 3 samples. Type: Other.
Allometric tissue-scale forces activate mechanoresponsive immune cells to determine pathological foreign body response to biomedical implants
GEO Series GSE227908. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Data associated with Automated Biomedical Text Classification with Research Domain Criteria
<p>Each file contains a set of abstracts for a given RDoC construct. Each file is named after one RDoC category. In each file, each line represents one PubMed abstract that belong to the RDoC category. Each line has a PubMeD ID and an abstract text separated by a tab. The dataset was created on August 2018. </p> <p>Please cite: M. Anani and I. Kahanda, Automated Biomedical Text Classification with Research Domain Criteria, International Conference on Bioinformatics and Computational Biology, Las Vegas, NV, 2018.</p>
Data from: A cross-lingual similarity measure for detecting biomedical term translations
Bilingual dictionaries for technical terms such as biomedical terms are an important resource for machine translation systems as well as for humans who would like to understand a concept described in a foreign language. Often a biomedical term is first proposed in English and later it is manually translated to other languages. Despite the fact that there are large monolingual lexicons of biomedical terms, only a fraction of those term lexicons are translated to other languages. Manually compiling large-scale bilingual dictionaries for technical domains is a challenging task because it is difficult to find a sufficiently large number of bilingual experts. We propose a cross-lingual similarity measure for detecting most similar translation candidates for a biomedical term specified in one language (source) from another language (target). Specifically, a biomedical term in a language is represented using two types of features: (a) intrinsic features that consist of character n-grams extracted from the term under consideration, and (b) extrinsic features that consist of unigrams and bigrams extracted from the contextual windows surrounding the term under consideration. We propose a cross-lingual similarity measure using each of those feature types. First, to reduce the dimensionality of the feature space in each language, we propose prototype vector projection (PVP)—a non-negative lower-dimensional vector projection method. Second, we propose a method to learn a mapping between the feature spaces in the source and target language using partial least squares regression (PLSR). The proposed method requires only a small number of training instances to learn a cross-lingual similarity measure. The proposed PVP method outperforms popular dimensionality reduction methods such as the singular value decomposition (SVD) and non-negative matrix factorization (NMF) in a nearest neighbor prediction task. Moreover, our experimental results covering several language pairs such as English–French, English–Spanish, English–Greek, and English–Japanese show that the proposed method outperforms several other feature projection methods in biomedical term translation prediction tasks.
Data from: It's all in the timing: calibrating temporal penalties for biomedical data sharing
Objective: Biomedical science is driven by datasets that are being accumulated at an unprecedented rate, with ever-growing volume and richness. There are various initiatives to make these datasets more widely available to recipients who sign Data Use Certificate agreements, whereby penalties are levied for violations. A particularly popular penalty is the temporary revocation, often for several months, of the recipient's data usage rights. This policy is based on the assumption that the value of biomedical research data depreciates significantly over time; however, no studies have been performed to substantiate this belief. This study investigates whether this assumption holds true and the data science policy implications. Methods: This study tests the hypothesis that the value of data for scientific investigators, in terms of the impact of the publications based on the data, decreases over time. The hypothesis is tested formally through a mixed linear effects model using approximately 1200 publications between 2007 and 2013 that used datasets from the Database of Genotypes and Phenotypes, a data-sharing initiative of the National Institutes of Health. Results: The analysis shows that the impact factors for publications based on Database of Genotypes and Phenotypes datasets depreciate in a statistically significant manner. However, we further discover that the depreciation rate is slow, only ∼10% per year, on average. Conclusion: The enduring value of data for subsequent studies implies that revoking usage for short periods of time may not sufficiently deter those who would violate Data Use Certificate agreements and that alternative penalty mechanisms may need to be invoked.
Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care
<p>Minimal dataset to replicate findings and figures for the publication Groh et al., Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care.</p>
WMT'16 Biomedical Translation Task - Medline parallel datasets
<p>Parallel data from Medline for the Biomedical Translation Task in the First Conference on Machine Translation (WMT 16) (http://www.statmt.org/wmt16/biomedical-translation-task.html).</p> <p>It contains parallel data for es/en, fr/en and pt/en.</p> <p>The documents were derived from the Medline/PubMed database (https://pubmed.ncbi.nlm.nih.gov/).</p>
Crux Biomedical Evaluation of the Crux Inferior Vena Cava Filter 4
ClinicalTrials.gov study NCT01120535. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Crux Biomedical Evaluation of the Crux Inferior Vena Cava Filter System 3 ("RETRIEVE 3")
ClinicalTrials.gov study NCT01120522. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Tissue Procurement for Biomedical Research
ClinicalTrials.gov study NCT00182858. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
480 Biomedical Bioresorbable Scaffold System in the Treatment of de Novo Superficial Femoral Artery (SFA) Lesions
ClinicalTrials.gov study NCT01403077. IPD Sharing: Not stated. Countries: 4. Publications: 0.
Electrochemical Behavior of Biomedical Alloys Exposed to Human Synovial Fluid
ClinicalTrials.gov study NCT04027231. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Crux Biomedical Vena Cava Filter Study - United States
ClinicalTrials.gov study NCT01120509. IPD Sharing: Not stated. Countries: 1. Publications: 0.
EVALUATION OF THE TOLERABILITY AND BIOMEDICAL POTENTIAL OF A GARMENT CONTAINING PRINTED CERAMICS IN MUSCULAR PAIN
ClinicalTrials.gov study NCT07274293. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.