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10 results for “association criteria”
Data from: Network structure and the optimisation of proximity-based association criteria
<ol> <li>Animal social network analysis (SNA) often uses proximity data obtained from automated tracking of individuals. Identifying associations based on proximity requires deciding on quantitative criteria such as the maximum distance or the longest time interval between visits of different individuals to still consider them associated. These quantitative criteria are not easily chosen based on <i>a priori</i> biological arguments alone.</li> <li>Here we propose a procedure for optimising proximity-based association criteria in SNA, whereby different spatial and temporal criteria are screened to determine which combination detects more network structure. If we assume that biologically-relevant associations among individuals are non-random, and that proximity data are mostly influenced by those associations, then it is logical to select criteria that minimise random associations and show the underlying network structure more clearly.</li> <li>We first used simulations to evaluate which of four simple descriptors of network structure remain unbiased (i.e., do not change directionally) when reducing the number of observations, since unbiased descriptors are necessary for comparing the structure of networks using different association criteria. Then, using two of those descriptors (coefficient of variation of the strength of associations, and network entropy), and empirical proximity data from automated tracking of common waxbills (<i>Estrilda astrild</i>) in a mesocosm environment, we found that the structure-based optimisation procedure selected the most biologically-relevant combination of spatial and temporal proximity criteria, in the sense that those criteria were also the best at distinguishing between previously known social sub-groups of individuals.</li> <li>These results indicate that, provided that the assumptions for structure-based optimisation are met, this procedure can find the most biologically-relevant association criteria. Thus, under the condition that proximity data are shaped by non-random social associations, and if using adequate descriptors of network structure, structure-based optimisation may be a useful tool for SNA, particularly when <i>a priori</i> biological arguments are insufficient to inform the choice of proximity-based association criteria.</li> </ol>
Data from: Network structure and the optimisation of proximity-based association criteria
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Criteria Associated With Patient Willingness to Participate in Biomedical Research
ClinicalTrials.gov study NCT03098303. IPD Sharing: Not stated. Countries: 1. Publications: 2.
ESMO-GROW checklist for the publication PD-1/PD-L1 blockade plus abnobaViscum® therapy is associated with improved survival in advanced or metastasized NSCLC patients, a real-world data registry study according to the ESMO-GROW criteria
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Figure 2 from: Khader H, Hasoun LZ, Alsayed A, Abu-Samak M (2021) Potentially inappropriate medications use and its associated factors among geriatric patients: a cross-sectional study based on 2019 Beers Criteria. Pharmacia 68(4): 789-795. https://doi.org/10.3897/pharmacia.68.e73597
Figure 2 Percentage of participants using potentially inappropriate medications (PIMs) based on 2019 American Geriatrics Society Beers criteria (AGS Beers criteria).
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>
Figure 1 from: Khader H, Hasoun LZ, Alsayed A, Abu-Samak M (2021) Potentially inappropriate medications use and its associated factors among geriatric patients: a cross-sectional study based on 2019 Beers Criteria. Pharmacia 68(4): 789-795. https://doi.org/10.3897/pharmacia.68.e73597
Figure 1 Number of medications used by participants. PRN: as needed.
Evaluating the Clinical Utility of Modified Ventilator-Associated Event Criteria in Predicting ICU Mortality and Ventilator Duration: Can Less Restrictive Definitions Improve Prediction?
ClinicalTrials.gov study NCT07212881. IPD Sharing: Not stated. Countries: 1. Publications: 0.
WHO Versus IADPSG Diagnostic Criteria of Gestational Diabetes Mellitus and Their Associated Maternal and Neonatal Outcomes
ClinicalTrials.gov study NCT02433262. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Association between Grazing and Food Addiction: The Italian Version of the Repetitive Eating Questionnaire (Rep(Eat)-Q) and Its Relationships with Food Addiction Criteria
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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.