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6,512 results for “clinical trial”
SMA TB Clinical trial - Soweto site - Short story
<p>In this video a nurse from SMA-TB clinical trial research team from South Africa shows one working day from Soweto, Baragwanath Hospital. She also gives insight about challenges of running a clinical trial during the COVID-19 pandemic. </p> <p>SMA-TB project has received funding from the European Union's Horizon 2020 research and innovation programme under grant ageement No 847762.</p>
SMA-TB Clinical trial research team's thoughts and opinions
<p>In this video SMA-TB Clinical trial research team members from Georgia and South Africa share their thoughts and opinions regarding the SMA-TB project and its impact both at scientific and personal level. </p> <p>SMA-TB team comprises of doctors, nurses, laboratory technicians and administrative. This video gives opportunity to look at and think of SMA-TB project from different perspectives. </p> <p>SMA-TB project has received funding from the European Union's Horizon 2020 research and innovation programme under grant ageement No 847762</p>
A web-based tool for automatically linking clinical trials to their publications - example calculation
<p><strong>Objective</strong>: Evidence synthesis teams, physicians, policy makers, and patients and their families all have an interest in following the outcomes of clinical trials and would benefit from being able to evaluate both the results posted in trial registries and in the publications that arise from them. Manual searching for publications arising from a given trial is a laborious and uncertain process. We sought to create a statistical model to automatically identify PubMed articles likely to report clinical outcome results from each registered trial in ClinicalTrials.gov.</p> <p><strong>Materials and Methods</strong>: A machine learning-based model was trained on pairs (publications linked to specific registered trials). Multiple features were constructed based on the degree of matching between the PubMed article metadata and specific fields of the trial registry, as well as matching with the set of publications already known to be linked to that trial.</p> <p><strong>Results</strong>: Evaluation of the model using NCT-linked articles as gold standard showed that they tend to be top ranked (median best rank = 1.0), and 91% of them are ranked in the top ten.</p> <p><strong>Discussion</strong>: Based on this model, we have created a free, public web based tool at http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi that, given any registered trial in ClinicalTrials.gov, presents a ranked list of the PubMed articles in order of estimated probability that they report clinical outcome data from that trial. The tool should greatly facilitate studies of trial outcome results and their relation to the original trial designs.</p>
Selected articles from the scoping review on the study designs for clinical trials applied to personalised medicine
<p>The dataset provides the data extracted for the scoping review of the literature on the study designs for clinical trials applied to personalised medicine, as part of the EU project on “Personalised Medicine Trials” (PERMIT).</p> <p>The dataset reports the references for all articles selected as part of the scoping review, as well as information on the general study characteristics and definition, methodology, statistical considerations, and examples of each study design referred to in each included paper.</p>
WikiProject Clinical Trials snapshot February 2022
<p><strong>About this record</strong></p> <p>This data supports "WikiProject Clinical Trials for Wikidata", a preprint at <a href="https://doi.org/10.1101/2022.04.01.22273328">https://doi.org/10.1101/2022.04.01.22273328</a> . The files in this record are a snapshot of the content output and appearance of WikiProject Clinical Trials in February 2022. Access the project at <a href="https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials">https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials</a> . The Jupyter Notebook in this record (1 WikiProject Clinical Trials 2022-02.ipynb) contains the project's example SPARQL queries from call Wikidata content, and the data files are the present results from those queries. As anyone can edit Wikidata and its content grows with time, query results will change over time.</p> <p><strong>Background</strong><br> Wikidata is a community and database within the Wikipedia ecosystem. WikiProject Clinical Trials is a community project in Wikidata to curate data related to clinical trials for its use in the Wikimedia platform or export to elsewhere.</p> <p><strong>Queries</strong></p> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Model_profiles">1 Model profiles</a> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_for_Zika_fever">1.1 Clinical trials for Zika fever</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_using_COVID-19_vaccine">1.2 Clinical trials using COVID-19 vaccine</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_at_Vanderbilt_University">1.3 Clinical trials at Vanderbilt University</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_with_Julie_McElrath_as_principal_investigator">1.4 Clinical trials with Julie McElrath as principal investigator</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_funded_by_Patient-Centered_Outcomes_Research_Institute">1.5 Clinical trials funded by Patient-Centered Outcomes Research Institute</a></li> </ul> </li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Topics_by_count_of_clinical_trials">2 Topics by count of clinical trials</a> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Medical_conditions">2.1 Medical conditions</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Research_interventions">2.2 Research interventions</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Research_sites">2.3 Research sites</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Principal_investigators">2.4 Principal investigators</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Funders">2.5 Funders</a></li> </ul> </li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Organizational_affiliations">3 Organizational affiliations</a> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_with_principal_investigator_and_their_affiliation">3.1 Clinical trials with principal investigator and their affiliation</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_where_principal_investigator_has_Vanderbilt_University_affiliation">3.2 Clinical trials where principal investigator has Vanderbilt University affiliation</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Chart_of_organizations_by_count_of_clinical_trials">3.3 Chart of organizations by count of clinical trials</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_where_the_sponsor_was_Pfizer">3.4 Clinical trials where the sponsor was Pfizer</a></li> </ul> </li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Researcher_demographics">4 Researcher demographics</a> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Count_of_principal_investigators_by_gender">4.1 Count of principal investigators by gender</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Clinical_trials_where_the_principal_investigator_is_female">4.2 Clinical trials where the principal investigator is female</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Principal_investigators_by_occupation">4.3 Principal investigators by occupation</a></li> </ul> </li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Scope_of_Wikidata's_clinical_trials_content">5 Scope of Wikidata's clinical trials content</a> <ul> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#List_of_clinical_trials">5.1 List of clinical trials</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Count_of_clinical_trials">5.2 Count of clinical trials</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Most_common_properties_applied_to_clinical_trials">5.3 Most common properties applied to clinical trials</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Count_of_statements_in_clinical_trial_records">5.4 Count of statements in clinical trial records</a></li> <li><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikiProject_Clinical_Trials/Query&oldid=1585305957#Count_of_trial_records_in_Wikidata_per_clinical_trial_registry">5.5 Count of trial records in Wikidata per clinical trial registry</a></li> </ul> </li> </ul> <p><strong>Online access</strong></p> <p>Again, the project at Wikidata is at <a href="https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials">https://www.wikidata.org/wiki/Wikidata:WikiProject_Clinical_Trials</a> . The Wikidata Query Service accessible through the "Query" page there assists users in modifying these or any queries to search for different targets, such as other medical conditions or institutions of interest. Another way to access the content online is by accessing the notebook through a copy in GitHub, such as at <a href="https://github.com/bluerasberry/WikiProject-Clinical-Trials">https://github.com/bluerasberry/WikiProject-Clinical-Trials</a> and rendering it through an online viewer, such as <a href="https://mybinder.org">https://mybinder.org</a> , or use the direct link <a href="https://mybinder.org/v2/zenodo/10.5281/zenodo.6317047/">https://mybinder.org/v2/zenodo/10.5281/zenodo.6317047/</a> .</p> <p><strong>Images</strong></p> <p>While Wikidata does retain historical versions which should be perpetually archived and available through the project page, this record contains image screenshots of the project as it appears now. For additional image metadata visit the image archives in Wikimedia Commons as linked here:</p> <ul> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_screenshot_2022-02.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_screenshot_2022-02.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_home.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_home.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_model.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_model.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_query.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_query.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_curate.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_curate.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_about.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_about.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_talk.png">https://commons.wikimedia.org/wiki/File:Wikidata_WikiProject_Clinical_Trials_-_screenshot_-_2022-02_-_talk.png</a></li> <li><a href="https://commons.wikimedia.org/wiki/File:Noun_clinical_benchmarking_1958245.svg">https://commons.wikimedia.org/wiki/File:Noun_clinical_benchmarking_1958245.svg</a>, image by Bold Yellow</li> </ul>
An annotated corpus of clinical trial publications supporting schema-based relational information extraction
<p>Repository of an annotated corpus of clinical trial abstracts supporting schema-based relational information extraction and the code for the inter-annotation agreement calculation and the baseline information extraction method.</p>
Rings in Clinical Trials and Drugs: Present and Future - Datasets
<p>"Rings in Clinical Trials and Drugs: Present and Future" - Datasets from publication in Journal of Medicinal Chemistry</p>
Classification of hierarchical text using geometric deep learning: the case of clinical trials corpus
<p>We consider the hierarchical representation of documents as graphs and use geometric deep learning to classify them into different categories. While graph neural networks can efficiently handle the variable structure of hierarchical documents using the permutation invariant message passing operations, we show that we can gain extra performance improvements using our proposed selective graph pooling operation that arises from the fact that some parts of the hierarchy are invariable across different documents. We applied our model to classify clinical trial (CT) protocols into completed and terminated categories. We use bag-of-words based as well as pre-trained transformer-based embeddings to featurize the graph nodes, achieving f1-scores $\simeq 0.85$ on a publicly available large scale CT registry of around 360K protocols. We further demonstrate how the selective pooling can add insights into the CT termination status prediction.</p>
Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial (Data for independent validation study)
<p>Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health relevant data from patients. However, to date, limited data and results have been published detailing real-world patient compliance, demonstrating accuracy in target indications or examining what novel insights and clinical value can be derived. Here we present novel, digital mobility data from two studies: an independent, non-interventional validation study with elderly, naturally slow walking subjects, and a global, multi-site phase IIb clinical trial involving patients with age-related muscle loss and slow walking speed (sarcopenia). Based on these data, we validate the accuracy of a novel algorithm for capturing in-clinic and real-world gait speed in frail, slow-walking adults. We demonstrate the feasibility of continuous monitoring with a wearable inertial sensor in elderly adults in real-world settings, and propose minimum thresholds for compliance required for robust capture of gait behaviors in this population. We also show how simple, inferred contextual information, describing the length of a given walking bout, can explain some of the variation in real-world gait speed, and use this information to demonstrate for the first time a relationship between in-clinic performance and real-world gait speed behavior. This work lays a foundation for exploration of the clinical relevance and value of such measures and is a first step in building a more complete chain of evidence between standardized physical performance assessment, real-world behavior, and subjective perceptions of mobility, independence and health.</p> <p>This dataset contains data collected during the independent validation study: derived data from raw accelerometry data, and summary performance data.</p> <p>The full dataset, including raw accelerometry data, is available here: <a href="https://mueller-et-al-2019.s3.amazonaws.com/index.html">https://mueller-et-al-2019.s3.amazonaws.com/index.html</a></p>
Data of 14 participants in the RCT titled Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial
<p>It is an Excel file including the numerical data of the 14 participants included in the study titled: <a name="_Hlk151119211"></a><span>Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial</span></p>
Questionnaire on gender and age-related peculiarities in informed consent to clinical trials – National legislation
<p>European experts from the six selected countries (Germany, Spain, Austria, France, Italy, and United Kingdom) included in research done within task 1.3 (Ethical and legal review of gender and age-related issues associated with the acquisition of informed consent) participated in a survey on gender and age-related peculiarities in informed consent to clinical trials within national legislations.</p> <p>Experts were selected for their high-level scientific expertise in the fields relevant to the objectives of task 1.3. A short questionnaire on “Gender and age-related peculiarities in informed consent to clinical trials within national legislations" has been prepared and circulated to contact experts. This questionnaire was meant to identify the legal review process and collect up-to-date data. It was structured in 10 queries, exclusively aimed at obtaining hard law and soft law information pertaining to the topics addressed in task 1.3.</p>
Analysis of websites, social media pages and apps for the development of new strategies for increasing participation of women in clinical trials
<p>For T2.5 of the i-CONSENT project, an analysis was undertaken of the strategies used to effectively communicate with women on the topic of women’s health or women’s health research, considering aspects such as tone, format and audience interaction. A total of 42 websites, social media pages and apps were included in the analysis. The attached document presents the findings from the data generation stage of this analysis.</p>
Clinical Trial Transparency at UK Universities (2018-2021)
<p>This dataset describes the analysis 20 U.K. universities' clinical trial registration and reporting policies and reporting performance of CTIMPs on EUCTR. This is supplementary information on a publication in the journal Clinical Trials: Journal of the Society for Clinical Trials. The manuscript is titled "Improving clinical trial transparency at U.K. universities: evaluating three years of policies and reporting performance on the European Clinical Trial Registry (EUCTR)". Please refer to the manuscript for more information on the methodology and analysis.</p>
Dataset from: Leveraging open tools to realize the potential of self-archiving: A cohort study in clinical trials
<p>This record includes the data associated with the study "Leveraging open tools to increase the potential of self-archiving to increase discoverability: A cohort study in clinical trials". The code used to generate these data is available under an open license in GitHub (<a href="https://github.com/delwen/oa-archiving-permissions">https://github.com/delwen/oa-archiving-permissions</a>). The deposit includes:</p> <p>- `intovalue.csv`: download of the IntoValue dataset (IntoValue 1 and IntoValue 2), which is actively maintained in GitHub (<a href="https://github.com/maia-sh/intovalue-data">https://github.com/maia-sh/intovalue-data</a>). The data was downloaded on 17 December 2022. More information on the generation of this dataset can be found at: <a href="https://doi.org/10.5281/zenodo.5141343">https://doi.org/10.5281/zenodo.5141343</a>. This data corresponds to the start of the trial screening flow diagram in the manuscript (n = 3,788).</p> <p>- `oa-unpaywall.csv`: dataset containing the results of the Unpaywall API query (query date: 17 December 2022). The dataset queried includes the following adaptations from `intovalue.csv`:</p> <ul> <li>As updated registry data had been downloaded on 1 November 2022, the IntoValue inclusion criteria were re-applied: <ul> <li>Interventional</li> <li>Study completion date between 2009 and 2017</li> <li>Complete based on study status</li> <li>Conducted by a German university medical center.</li> </ul> </li> <li>The dataset was further limited to: <ul> <li>Unique trials (trials from IntoValue 2 were preserved)</li> <li>Unique publications with a DOI</li> </ul> </li> </ul> <p>- `oa-syp-permissions.csv`: dataset containing the results of the Shareyourpaper API query (query date: 17 December 2022). The dataset queried is the same as in `oa-unpaywall.csv`.</p> <p>- `oa-merged-data.csv`: dataset containing the merged Unpaywall and Shareyourpaper data for all clinical trial results publications considered in this study. The dataset was further limited to journal articles that resolved in Unpaywall and were published between 2010 - 2020 (based on the publication date in Unpaywall). This is the main dataset underlying the analyses in the manuscript.</p>
Data and Code Supplement to: "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression"
<p>Dataset to support secondary analyses reported in "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression" in the Journal of Consulting and Clinical Psychology</p>
VISION Invited lecture - New Perspectives in Clinical Trials
<p>Recording and presentation of the invited lecture that took place online on 15 June 2022 - <strong>Prof. Stefano Bonassi, Ph.D., ERT - New Perspectives in Clinical Trials</strong>.</p> <p>Clinical trials are our best approach to generate clinical evidence. Since the early stages in the first decades of the past century, clinical trial has been in continuous evolution. Innovation has interested the formulation of stopping guidelines for safety, efficacy, and futility; the use of internet, changes in the way the informed consent is requested, the introduction of pragmatic trials, the challenge of personalized medicine, the concept of non-inferiority, and many others. Today, trials range from a single person to hundred-thousand people, from a single lab to hundreds of centers around the world, from simple two-arm randomizations to increasingly complex study designs. The lecture will address issues related to the performance of clinical trials, how to deal with the increasing use of the internet, the dramatic change concerning ethics in clinical studies.</p>
Confirmation of the suitability and stability of the imatinib mesylate drug product formulation for intravenous administration in the INVENT-COVID clinical trial
<p>Abstract:</p> <p>An isotonic sterile aqueous solution of imatinib mesylate was formulated and then manufactured according to cGMP by KABS Laboratories. A solution pH of 5.0 is optimum for imatinib mesylate solubility and stability and this is maintained by a sodium acetate buffer. The drug product for the clinical study was presented as a sterile solution in a Type 1 clear glass vial with chlorobutyl stopper and seal. Stability studies on the drug product have confirmed an excellent stability profile and these data are presented in Table 1. The drug product specification detailed in this table is consistent with Regulatory Authority requirements for this stage in clinical development. These data support the conclusion that the drug product used in the INVENT-COVID trial was fully compliant with all cGMP and EU Regulatory Authority requirements.</p> <p> </p>
Dataset related to article "Harmonization of sensorimotor deficit assessment in a registered multicentre pre-clinical randomized controlled trial using two models of ischemic stroke"
<p>https://figshare.com/search?q=10.6084%2Fm9.figshare.21346731</p>
Clinical Trials_Original dataset. Rising Pharmaceutical Innovation in the Global South.
<p>This is a supplementary document of the research reports from the "Research Collaboration on Technology, Equity, and the Right to Health", between the Global Health Centre (GHC) at the Geneva Graduate Institute in Switzerland, the James P. Grant School of Public Health at BRAC University in Bangladesh, and the Universidad de los Andes (ANDES) in Colombia, supported by the Open Society University Network (OSUN). For more information please refer to: Knowledge Portal on Innovation and Access to Medicines - https://www.knowledgeportalia.org/. </p>
Clinical trials analysis results. Rising pharmaceutical innovation in the Global South.
<p>This is a supplementary document of the research reports from the "Research Collaboration on Technology, Equity, and the Right to Health", between the Global Health Centre (GHC) at the Geneva Graduate Institute in Switzerland, the James P. Grant School of Public Health at BRAC University in Bangladesh, and the Universidad de los Andes (ANDES) in Colombia, supported by the Open Society University Network (OSUN). For more information please refer to: Knowledge Portal on Innovation and Access to Medicines - <a href="https://www.knowledgeportalia.org/">https://www.knowledgeportalia.org/</a></p>
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.