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6,512 results for “clinical trial”
Prognostic Value of High-Sensitive C-Reactive Protein in patients with In-Stent Restenosis: A Meta-Analysis of Clinical Trials
<p>Supplement figures</p>
SemEval 2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials
<p>This is the github repository hosting data and code for Task 2: Safe Biomedical Natural Language Inference for Clinical Trials at <a href="https://semeval.github.io/SemEval2024/" rel="nofollow">Semeval 2024</a>.</p> <p>For additional information about the task, please consult the official <a href="https://sites.google.com/view/nli4ct/home" rel="nofollow">website</a>.</p>
Dataset for Spence et al., "Patient consent to publication and data sharing in industry and NIH-funded clinical trials" (Trials 2018 19:269).
<p>Dataset for our journal publication (Spence et al. 2018 <a href="https://doi.org/10.1186/s13063-018-2651-2">https://doi.org/10.1186/s13063-018-2651-2</a>). This dataset contains</p> <ul> <li>Informed consent forms (ICFs) for 98 industry-funded clinical trials</li> <li>Informed consent forms (ICFs) for 46 NIH-funded clinical trials</li> <li>Our extraction datasheet</li> </ul>
Clinical Performance of Dental Implants Following Sinus Floor Augmentation: A Systematic Review and Meta-Analysis of Clinical Trials with at Least 3 Years of Follow-u
<p>Dataset for all analyses of the paper, original Figures (contour-enhanced forest plots) that were adapted by the journal, and supplementary appendices that were cut by the journal during post-acceptance typesetting.</p>
Direct pulp capping versus pulpotomy with MTA for carious primary molars: a 3-year randomised clinical trial
<p>Dataset for the analyses of the trial.</p>
Radix Sophorae flavescentis for chronic hepatitis B - Characteristics of potential randomised clinical trials
<p>This table listed the references considered to be potential randomised clinical trials on Radix Sophorae flavescentis for chronic hepatitis B, as we could not attain any response from the authors about their randomisation method. We also listed the results of contacting authors. </p> <p> </p>
Data From: ChatGPT versus expert feedback on clinical reasoning questions and their effect on learning: a randomized controlled trial
<p>Dataset Info</p> <p><strong>1) Immediate Test</strong><br>- The first row of the dataset identifies the columns.<br>- Column A represents the participants’ iDs.<br>- Column B represents the participants’ assigned group [0: Control (ExpertFeedback) 1: Intervention (ChatGPTFeedback)].<br>- Column C represents the genders of the participants (1: Female, 2: Male).<br>- Column D represents the first-year repetition status of the participants. (0: No, 1: Yes)<br>- Column E to H represent the scores in four different uncomplicated urinary tract infection (UTI) Key-Features Questions Items separately. <br>- Column I represents the total scores in uncomplicated UTI Key-Features Questions Items. <br>- Column J to M represent the scores in four different complicated UTI Key-Features Questions Items separately. <br>- Column N represents the total scores in complicated UTI Key-Features Questions Items. <br>- Column O to R represent the scores in four different pyelonephritis Key-Features Questions Items separately. <br>- Column S represents the total scores in pyelonephritis Key-Features Questions Items. <br>- Column T represents the total scores in immediate test. </p> <p><strong>2) Delayed Test</strong><br>- The first row of the dataset identifies the columns.<br>- Column A represents the participants iDs.<br>- Column B represents the participants’ assigned group [0: Control (ExpertFeedback) 1: Intervention (ChatGPTFeedback)].<br>- Column C represents the genders of the participants (1: Female, 2: Male).<br>- Column D represents the first-year repetition status of the participants. (0: No, 1: Yes)<br>- Column E to H represent the scores in four different uncomplicated urinary tract infection (UTI) Key-Features Questions Items separately. <br>- Column I represents the total scores in uncomplicated UTI Key-Features Questions Items. <br>- Column J to M represent the scores in four different complicated UTI Key-Features Questions Items separately. <br>- Column N represents the total scores in complicated UTI Key-Features Questions Items. <br>- Column O to R represent the scores in four different pyelonephritis Key-Features Questions Items separately. <br>- Column S represents the total scores in pyelonephritis Key-Features Questions Items. <br>- Column T represents the total scores in delayed test. </p> <p><strong>3) Pre-Intervention Survey on Critical Approach to AI</strong><br>- The first row of the dataset identifies the columns.<br>- Column A represents the participants iDs.<br>- Column B represents the participants’ assigned group [0: Control (ExpertFeedback) 1: Intervention (ChatGPTFeedback)].<br>- Column C represents the genders of the participants (1: Female, 2: Male).<br>- Column D represents the first-year repetition status of the participants (0: No, 1: Yes).<br>- Column E to J represent the responses of the participants to survey questions before the intervention. Each column is evaluated on a scale from 1 to 7. As it progresses from 1 to 7, the agreement status of participants to survey questions increases. (1: No agreement at all, 7: completely agree)</p> <p><strong>4) Post-Intervention Survey on Critical Approach to AI</strong><br>- The first row of the dataset identifies the columns.<br>- Column A represents the participants iDs.<br>- Column B represents the participants’ assigned group [0: Control (ExpertFeedback) 1: Intervention (ChatGPTFeedback)].<br>- Column C represents the genders of the participants (1: Female, 2: Male).<br>- Column D represents the first-year repetition status of the participants (0: No, 1: Yes).<br>- Column E to J represent the evaluation of the participants to survey questions after intervention. Each column is evaluated on a scale from 1 to 7. As it progresses from 1 to 7, the agreement status of participants to survey questions increases. (1: No agreement at all, 7: completely agree)</p>
Endorsement of reporting guidelines and clinical trial registration across urological medical journals: a cross-sectional study
Open the record for dataset details and reuse information.
Clinical Trials Transformation Initiative's (CTTI) Trial Information through September 2024
<p>A static copy of the AACT database (Pipe-Delimited Files). Monthly Archive of Static Copies: 20240927_export_ctgov.zip from https://aact.ctti-clinicaltrials.org/download. </p>
Clinical Trial Transparency and Data-Sharing Among Bio-Pharmaceutical Companies and the Role of Company Size, Location, and Product Type: A Cross-Sectional Descriptive Analysis
<p><b>Objective</b>: To examine company characteristics associated with better transparency and to apply a tool used to measure and improve clinical trial transparency among large companies and drugs, to smaller companies and biologics.</p> <p><b>Design</b>: Cross-sectional descriptive analysis.</p> <p><b>Setting and participants. </b>Novel drugs and biologics FDA approved in 2016 and 2017, and their company sponsors.</p> <p>Using established Good Pharma Scorecard (GPS) measures, companies and products were evaluated on their clinical trial registration, results dissemination, and FDA Amendments Act (FDAAA) implementation; Companies were ranked using these measures and a multi-component data sharing measure. Associations between company transparency scores with company size (large vs non-large), location (US vs non-US), and sponsored product type (drug vs biologic) were also examined. 26% of products (16/62) had publicly available results for all clinical trials supporting their FDA approval and 67% (39/58) had public results for trials in patients by 6 months after their FDA approval; 58% (32/55) were FDAAA compliant. Large companies were significantly more transparent than non-large companies (overall median transparency score of 95% [IQR 91-100] vs 59% [IQR 41-70], p<0.001), attributable to higher FDAAA compliance (median of 100% [IQR 88-100] vs 57% [0-100], p=0.01) and better data sharing (median of 100% [IQR 80-100] vs 20% [IQR 20-40], p<0.01). No significant differences were observed by company location or product type. It was feasible to apply the GPS transparency measures and ranking tool to non-large companies and biologics. Large companies are significantly more transparent than non-large companies, driven by better data sharing procedures and implementation of FDAAA trial reporting requirements. Greater research transparency is needed, particularly among non-large companies, to maximize the benefits of research for patient care and scientific innovation. </p>
Design and implementation of a national clinical trials registry
<p>The authors have developed a Web-based system that provides summary information about clinical trials being conducted throughout the United States. The first version of the system, publicly available in February 2000, contains more than 4,000 records representing primarily trials sponsored by the National Institutes of Health. The impetus for this system has come from the Food and Drug Administration (FDA) Modernization Act of 1997, which mandated a registry of both federally and privately funded clinical trials “of experimental treatments for serious or life-threatening diseases or conditions.” The system design and implementation have been guided by several principles. First, all stages of system development were guided by the needs of the primary intended audience, patients and other members of the public. Second, broad agreement on a common set of data elements was obtained. Third, the system was designed in a modular and extensible way, and search methods that take extensive advantage of the National Library of Medicine's Unified Medical Language System (UMLS) were developed. Finally, since this will be a long-term effort involving many individuals and organizations, the project is being implemented in several phases.</p>
CONSORT Checklist for The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial
<p>CONSORT Checklist for The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial</p>
The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial
<p>The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial</p>
Efficacy of Sealing Molars: Split-mouth Randomized Clinical Trial
ClinicalTrials.gov study NCT03819868. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
An Observational Exploration of Clinical Trials Targeting Traumatic Brain Injury
ClinicalTrials.gov study NCT06264518. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Clinical Trial of FCN-437c Capsule in Patients With Hepatic Insufficiency
ClinicalTrials.gov study NCT06620731. IPD Sharing: NO. Countries: 1. Publications: 1.
DNA Methylation Analysis in Acute Coronary Syndrome and Atrial Fibrillation: DIANA Clinical Trial
ClinicalTrials.gov study NCT04371809. IPD Sharing: NO. Countries: 1. Publications: 2.
Tunnel Technique With Emdogain® in Addition to Connective Tissue Graft Compared With Connective Tissue Graft Alone for the Treatment of Gingival Recessions: a Randomized Clinical Trial.
ClinicalTrials.gov study NCT03354104. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Pilot Clinical Trial of Sympathetic Blockade With Botulinum Toxin Type A to Treat Complex Regional Pain Syndrome (CRPS): a Randomized, Double-Blind, Controlled, Crossover Trial.
ClinicalTrials.gov study NCT00637533. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Clinical Trial of Phenformin in Combination With BRAF Inhibitor + MEK Inhibitor for Patients With BRAF-mutated Melanoma
ClinicalTrials.gov study NCT03026517. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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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.