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33
datasets available to search
ShareScore release 0.9.0
Dataset results
33 results for “family physicians”
Improving the Care of Diabetic Patients: A Randomized Trial of a Family Physician Office-Based Chronic Disease Care Model for Patients With Type 2 Diabetes
ClinicalTrials.gov study NCT00789282. IPD Sharing: Not stated. Countries: 1. Publications: 0.
CHOICES: Family Physicians Treat Overweight Children
ClinicalTrials.gov study NCT01674920. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Impact Of Physician Communication On Family Inpatient Experience
ClinicalTrials.gov study NCT01298791. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of an Interventional Program for Family Physicians on Well-child Care for Children Under-5
ClinicalTrials.gov study NCT03976778. IPD Sharing: YES. Countries: 1. Publications: 0.
Difference Between Patient Vaccine Hesitancy and Perception by Their Family Physician of Their Vaccine Hesitancy
ClinicalTrials.gov study NCT04313816. IPD Sharing: NO. Countries: 1. Publications: 0.
Enabling Family Physicians to Reduce Vaccine Hesitancy and Increase Covid-19 Vaccine Uptake
ClinicalTrials.gov study NCT04963790. IPD Sharing: NO. Countries: 1. Publications: 0.
Pharmacist and Family Medicine Physician Collaboration for Pre-Visit Planning and Team Huddles for CCM Patients
ClinicalTrials.gov study NCT04342338. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Sensitivity of Antibiotics for Urinary Tract Infections Patients Attending Family Physicians
ClinicalTrials.gov study NCT02305342. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Benefits of the Involvement of Nurses in Meetings Between Physicians and the Families of Patients in the ICU.
ClinicalTrials.gov study NCT01745406. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Management of Gestational Weight Gain by Family Physicians: Seeking Congruence With Guidelines
ClinicalTrials.gov study NCT01803698. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Exploring the perceptions of physicians, caregivers and families towards artificial nutrition and hydration for people in permanent vegetative state: how can a photo-elicitation method help?
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Journal articles published by family and community physicians from Brazil up to 2018
<p>Data on articles published by family in commnity from Brazil up to 2018. See articles <a href="https://doi.org/10.1136/fmch-2020-000321">Fontenelle, Rossi, et al. (2020)</a> and <a href="https://doi.org/10.5712/rbmfc16(43)2589">Fontenelle et al. (2021)</a> to understand how the dataset was compiled from the data sources.</p> <p>This is a semicolon-separated CSV file with a byte-order mark, so that it can be openned by Microsoft Excel users in Brazil. Users of LibreOffice Calc and dedicated statistical software should be able do adapt without trouble. The accompanying data dictionary is recorded in the same format.</p> <p>The CNPq ID number links to the dataset <a href="https://doi.org/10.5281/zenodo.3376310">Fontenelle et al. (2019)</a>, and the NLM ID string links to the dataset <a href="https://doi.org/10.5281/zenodo.4459429">Fontenelle, Oliveira et al. (2021)</a>.</p>
Postgraduate education among family and community physicians in Brazil: the Trajetórias MFC project
<p>Dataset analyzed in the "Postgraduate education among family and community physicians in Brazil: the <em>Trajetórias MFC</em> project" manuscript.</p> <p>File "family_physicians" has personally identifiable data on family and community physicians in Brazil, more specifically on their specialization (medical residency, specialist certification) and their master's and PhD degrees. File "postgraduate_programs" has data on the master's and PhD programs the family and community physicians graduated from.</p> <p>All spreadsheets are in the CSV (comma-separated values) format, delmited with semicolons and encoded in UTF-8 (there are special characters due to the Portuguese language) with the byte-order mark (BOM). The spreadsheets can be opened with desktop or Web application software (LibreOffice Calc, Microsoft Excel, Google Sheets) or with statistical software such as R. Each dataset is accompanied with a data dictionary for interpreting the columns. See also the manuscript for background.</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.