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28,650 results for “trial”
ACF database on the vitamin A and iron outcomes from the MANGO trial
<p>This dataset contains the variables used in the analysis of the vitamin A and iron outcomes of the MANGO trial carried out in Burkina Faso between 2016 and 2018. </p>
MiRoR7-P1- Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design
<p>dataset referring to </p> <p><strong>Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design</strong></p> <p> </p> <p> </p> <p>Lorenzo Bertizzolo<sup>1</sup>, Patrick M Bossuyt<sup>2</sup>, Ignacio Atal<sup>1, 5</sup>, Philippe Ravaud<sup>1, 3-6</sup>, Agnès Dechartres<sup>7</sup></p> <p> </p> <p><sup>1</sup> INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.</p> <p><sup>2</sup> Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.</p> <p><sup>3</sup> Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.</p> <p><sup>4</sup> Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.</p> <p><sup>5</sup> Cochrane France, Paris, France</p> <p><sup>6</sup> Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA</p> <p><sup>7</sup> Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France</p>
Data relating to Clyne et al. Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study
<p>Data relating to the study reported in the paper "Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study".</p>
Experimental data of the paper "Trial-based Heuristic Tree Search for MDPs with Factored Action Spaces"
<p>This data set contains the code of our planner and of the planner that was used as baseline, the benchmark set that was used to perform experiments as well as the parsed values and basic reports that are reported in the paper. More information can be found in the README that is also included.</p>
FLAME Project, Open Call 3, FC5 Live Trial
<p>This dataset contains the RAW data recorded during the FC5 Live trial, Open Call 3, FLAME project.<br> The dataset contains the following data:<br> • Server-side metrics: log data of all involved nodes from CLMC (CPU, mem used, bandwidth used)<br> • Client-side metrics: Bitrate, latency, and buffering<br> • Users’ feedback: questionnaires (CSV)</p>
Analysis of human humoral responses in a typhoid vaccine efficacy trial used for SIMON analysis
<p>The VAST dataset contains data from 72 individuals enrolled in the clinical study to evaluate humoral responses in a typhoid vaccine efficacy trial in a controlled human <em>Salmonella </em>Typhi infection model (see original publication: <a href="https://doi.org/10.3389/fimmu.2019.02582">https://doi.org/10.3389/fimmu.2019.02582</a>). Only day 0 (day of the challenge) log-transformed data were used in the SIMON analysis, as described in the publication (<a href="https://doi.org/10.1101/2020.08.16.252767">https://doi.org/10.1101/2020.08.16.252767</a>). Individuals were vaccinated with either a purified Vi polysaccharide (Vi-PS) vaccine (35 individuals) or the Vi tetanus toxoid conjugate (Vi-TT) vaccine (37 individuals) one month prior to oral challenge with live <em>Salmonella </em>Typhi. Out of 72 individuals, 26 developed an acute typhoid infection following the challenge.</p>
COVID19 - Clinical Trials
<p> </p> <p>The objective of the project is to extract a set of clinical trials carried out for Covid-19 disease around the world in order to carry out statistical and data mining studies .</p> <p>The <a href="https://clinicaltrials.gov/">ClinicalTrials.gov</a> website is a database of privately and publicly clinical trials conducted around the world.</p> <p>The URL of the project to extract the data is the GitHub <a href="https://github.com/jordi-puig/web-scraping">repository</a>.</p>
Forward selection in a maritime pine polycross progeny trial using pedigree reconstruction.
<p>These two excel files gather genotyping data used in the following publication:</p> <p>Vidal M, Plomion C, Raffin A, Harvengt L, Bouffier L (2017) Forward selection in a maritime pine polycross progeny trial using pedigree reconstruction. Annals of Forest Science, 74(1). DOI 10.1007/s13595-016-0596-8</p> <p>The dataset describes genotyping profiles (with 56 or 63 SNPs) for the G1 and G2 individuals sampled in this paper. For each individual, the following information is mentioned: identity, preselection option (only for G2 individuals), the generation to which the individual belongs, pedigree (only for G2 individuals), alleles for each SNP.</p>
Embodied Spatial Navigation Training in Mild Cognitive Impairment: A Proof-of-Concept Trial
<p>Raw data of included cognitive test and VR data Starting Grant Ricerca Finalizzata, code: SG-2018-12368175</p>
Kuopio gait dataset: motion capture, inertial measurement and video-based sagittal-plane keypoint data from walking trials
<p>This dataset contains motion capture (3D marker trajectories, ground reaction forces and moments), inertial measurement unit (wearable Movella Xsens MTw Awinda sensors on the pelvis, both thighs, both shanks, and both feet), and sagittal-plane video (anatomical keypoints identified with the OpenPose human pose estimation algorithm) data.<br>The data is from 51 willing participants and collected in the HUMEA laboratory in the University of Eastern Finland, Kuopio, Finland, between 2022 and 2023. All trials were conducted barefoot.</p> <p>The file structure contains an Excel file containing information of the participants, data folders under each subject (numbered 01 to 51), and a MATLAB script.</p> <p>The Excel file has the following data for the participants:</p> <ul> <li><strong>ID</strong>: ID of the participants from 1 to 51</li> <li><strong>Age</strong>: age of the participant in years</li> <li><strong>Gender</strong>: biological sex as M for male, F for female</li> <li><strong>Leg</strong>: the participant's dominant leg, identified by asking which foot the participant would use to kick a football; R for right, L for left</li> <li><strong>Height</strong>: height of the participant in centimeters</li> <li><strong>Invalid_trials</strong>: list of invalid trials in the motion capture data (MOCAP) data, usually classified as such because the participant did not properly step on the middle force plate</li> <li><strong>IAD</strong>: inter-asis distance in millimeters, the distance between palpated left and right anterior superior iliac spine, measured with a caliper</li> <li><strong>Left_knee_width</strong>: width of the left knee from medial epicondyle to lateral epicondyle in millimeters, palpated and measured with a caliper</li> <li><strong>Right_knee_width</strong>: same as above for the right knee</li> <li><strong>Left_ankle width</strong>: width of the left ankle from medial malleolus to lateral malleolus in millimeters, palpated and measured with a caliper</li> <li><strong>Right_ankle_width</strong>: same as above for the right ankle</li> <li><strong>Left_thigh_length</strong>: the distance between the greater trochanter of the left femur and the lateral epicondyle of the left femur in millimeters, palpated and measured with a measuring tape</li> <li><strong>Right_thigh_length</strong>: same as above for the right thigh</li> <li><strong>Left_shank_length</strong>: the distance between the medial epicondyle of the femur and the medial malleolus of the tibia in millimeters, palpated and measured with a measuring tape</li> <li><strong>Right_shank_length</strong>: same as above for the right shank</li> <li><strong>Mass</strong>: mass in kilograms, measured on a force plate just before the walking measurements</li> <li><strong>ICD</strong>: inter-condylar distance of the knee of the dominant leg, measured from low-field MRI</li> <li><strong>Left_knee_width_mocap</strong>: distance between reflective MOCAP markers on the medial and lateral epicondyles of the knee in millimeters, measured from a static standing trial; -1 for missing (subject did not have those markers)</li> <li><strong>Right_knee_width_mocap</strong>: same as above for the right knee</li> </ul> <p>The folders under each subject (folders numbered 01 to 51) are as follows:</p> <ul> <li><strong>imu</strong>: "Raw" inertial measurement unit (IMU) data files that can be read with Xsens Device API (included in Xsens MT Manager 4.6, which may be unavailable these days, not sure). You won't need this if you use the data in the imu_extracted folder.</li> <li><strong>imu_extracted</strong>: IMU data extracted from those data files using the Xsens Device API, so you don't have to. <ul> <li>The data is saved as MATLAB structs where the fields are named as a sensor ID (e.g., "B42D48"). The sensor IDs and their corresponding IMU locations are as follows: <ul> <li>pelvis IMU: B42DA3</li> <li>right femur IMU: B42DA2</li> <li>left femur IMU: B42D4D</li> <li>right tibia IMU: B42DAE</li> <li>left tibia IMU: B42D53</li> <li>right foot IMU: B42D48</li> <li>left foot IMU: B42D51 (except for subjects 01 and 02, where left foot IMU has the ID B42D4E)</li> </ul> </li> <li>Some of the data are just zeros as they couldn't be read from these sensors, but under each sensor, the fields "calibratedAcceleration", "freeAcceleration", "time", "rotationMatrix", and "quaternion" contain usable data. <ul> <li>time: Contains time stamps of the measurement at each frame recorded at 100 Hz, so if you remove the first value from all values in the time vector and divide the result by 100, you will get the time in seconds from the beginning of the walking trial.</li> <li>calibratedAcceleration and freeAcceleration: Contain triaxial acceleration data from the accelerometers of the IMU. freeAcceleration is just calibratedAcceleration without the effect of Earth's gravitational acceleration.</li> <li>rotationMatrix: Orientations of the IMU as rotation matrices.</li> <li>quaternion: Orientations of the IMU as quaternions.</li> </ul> </li> </ul> </li> <li><strong>openpose</strong>: Trajectories of the keypoints identified from sagittal plane video frames, saved as json files. <ul> <li>The keypoints are from the BODY_25 model of OpenPose (https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/md_doc_02_output.html).</li> <li>Each frame in the video has its own json file.</li> <li>You can use the function in the script "OpenPose_to_keypoint_table.m" in the root folder to read the keypoint trajectories and confidences of all frames in a walking trial into MATLAB tables. The function takes as argument the path to the folder containing the json files of the walking trial.</li> </ul> </li> <li>Note that some subjects (11, 14, 37, 49) do not have keypoint and IMU data.</li> </ul> <p>The folders under each subject are divided into three ZIP archives with 17 subjects each.</p> <p>The script "OpenPose_to_keypoint_table.m" is a MATLAB script for extracting keypoint trajectories and confidences from JSON files into tables in MATLAB.</p> <p><br><strong>Publication in Data in Brief</strong>: <a href="https://doi.org/10.1016/j.dib.2024.110841" target="_blank" rel="noopener">https://doi.org/10.1016/j.dib.2024.110841</a></p> <p><br><strong>Contact</strong>: Jere Lavikainen, jere.lavikainen@uef.fi</p>
SHOCK Trial - Early Revascularization in Acute Myocardial Infarction Complicated by Cardiogenic Shock
<p>The leading cause of death in patients hospitalized for acute myocardial infarction is cardiogenic shock. We conducted a randomized trial to evaluate early revascularization in patients with cardiogenic shock. In patients with cardiogenic shock, emergency revascularization did not significantly reduce overall mortality at 30 days. However, after six months there was a significant survival benefit. Our conclusion was that early revascularization should be strongly considered for patients with acute myocardial infarction complicated by cardiogenic shock. We are making original data that was collected for this trial available here for further analysis.</p>
SMA-TB Clinical trial: video & electronic informed consent
<p>The first SMA-TB video has been produced aiming a better understanding of SMA-TB Randomized Clinical Trial (RCT) objectives and procedures. This RCT is work package 1 of SMA-TB project. It is entitled <em>"Phase 2b Randomized double-blind, placebo controlled trial to estimate the potential efficacy and safety of two repurposed drugs, acetylsalicylic acid and ibuprofen, for use as adjunct therapy added to, and compared with, the standard WHO recommended TB regimen (SMA-TB)”, </em>and is registered in ClinicalTrials.gov data under identifier NCT04575519</p> <p>This video has been conceptualized as an e-informed consent for TB patients aiming their participation in SMA-TB CTs in Georgia and South Africa, as well as for anyone wanting to learn about the SMA-TB CT. The video explains in a very comprehensive way the rationale of SMA-TB concept, how the CT will be performed, what is expected from the patient, which are potential benefits, as well as side effects. The message is produced both in English and in Georgian.</p>
2021 5Genesis Berlin Platform Field Trial RTT and Throughput Measurements
<p>RTT and Throughput measurements from the various measurement endpoints of the 2021 5GENESIS Berlin Platform Field Trials at IHP, in Frankfurt (Oder).</p>
Data from 18 fungicide trials on potato late blight in UK and Ireland 2013-2017
<p>The data set comprises records of disease incidence, crop growth stage and yield from untreated and treated plots.</p> <p>The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file.</p> <p>The field trials were conducted by Corteva Agriscience, Germany.</p>
Data from 168 fungicide trials in wheat fields across Europe 2014-2018
<p>The data set comprises records of disease incidence, crop growth stage and yield from untreated and treated plots.</p> <p>The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file.</p> <p>The field trials were conducted by Corteva Agriscience, Germany.</p>
Data from 56 fungicide trials in wheat fields across Europe 2017-2019
<p>The data set comprises records of disease incidence and yield from untreated and treated plots.</p> <p>The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file.</p> <p>The field trials were conducted by BASF, Germany.</p>
Data from 89 fungicide trials on apple scab across Europe 2008-2018
<p>The data set comprises records of disease incidence and yield from untreated and treated plots.</p> <p><strong>Assessments</strong><br> The disease infection was expressed as the intensity of attack (=severity) and/or the frequency of attack. Two assessment methods were used:</p> <p>1. Visual assessment:<br> • P%INF: intensity of attack was obtained as a visual estimation of the percentage of each plant part (leaves or fruits) affected by disease<br> • P%FREQ: frequency of attack was represented by the number of infected leaves or fruits. The frequency is expressed as a percentage of the number sampled.</p> <p><br> 2. Class assessment<br> The level of the attack (intensity and frequency) was evaluated and calculated by classing plants into different severity categories ranging from no disease to severe attack.<br> • BEFHKT: frequency of disease attack expressed as a percentage, considering 4 damage classes<br> • BEFWER: intensity of attack expressed as a percentage, considering 4 damage classes.</p> <p>BEFHKT = 100*(cl2 + cl3 + cl4)/(cl1 + cl2 + cl3 + cl4)<br> BEFWER = 100*(cl2 + 2*cl3 + 3*cl4)/(3*N) (the Townsend-Heuberger intensity of attck)</p> <p><strong>Table of measures</strong><br> Measure Description<br> P%FREQ Estimated frequency of attack %<br> P%INF Estimated severy of attack %<br> %ANTK1 Class 1 (%)<br> %ANTK2 Class 2 (%)<br> %ANTK3 Class 3 (%)<br> %ANTK4 Class 4 (%)<br> BEFHKT Frequency of attack<br> BEFWER Index of attack<br> INFECT Infection (F); Infestation (F)<br> KR%ABB Diseased (%)<br> WIRKGR Percent of untreated</p> <p><strong>Data format and source</strong><br> The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file.</p> <p>The field trials were conducted by BASF, Germany.</p> <p> </p>
Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231) - Variant Calls
<p>Variant Calls from Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231)</p> <p>See publication for methodology.</p>
Faba Beans in Pig Feeding Trials
<p>Dr. Peadar Lawlor, Teagasc and John Ryan of Adesco talk to Tim O'Donovan of Seedtech about their research into feeding faba beans instead of imported protein to pigs. The video is an output of the Legumes Translated Horizon 2020 project and is available in English with subtitled in English and German. </p>
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resource Entity Extraction Using Clinical Trials Literature
<p><strong>Datasets</strong></p> <ol> <li>DISTANT-CTO is a weakly-labelled dataset of 'Intervention' and 'Comparator' entity annotated sentences. The dataset was obtained using candidate generation the approach described in "DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low Resource Entity Extraction Using Clinical Trials Literature". <ol> <li>distantcto_high_conf.txt - ds conf 1.0 (full dataset)</li> <li>extraction1_pos_posnegtrail_conf09.txt - ds conf 0.9 (partial dataset)</li> </ol> </li> <li>The physio test set is a dataset comprising 153 PICO annotated randomized controlled trial abstracts from Physiotherapy and Rehabilitation. This dataset was used as an additional benchmark to evaluate the generalization power of the weakly annotated dataset and NER model for this sub-domain.</li> </ol> <p> </p> <p><strong>Utility</strong></p> <p>The dataset could be used as an input for training 'Intervention' named-entity recognition (NER) models.</p> <p> </p> <p><strong>Availability</strong></p> <p>This directory includes extraction1_pos_posnegtrail_conf09.txt - This text data file contains all the weak annotations (source intervention terms mapped onto target sentences) from clinicaltrials.org (CTO) with a confidence score of 0.9 and above.</p> <p>The directory also includes ‘physio_sent_annot2POS_posnegtrail.txt’ – This data file contains manually annotated (Intervention entity) data from the physiotherapy and rehabilitation domain. It follows a roughly similar structure as described in the ‘Description for long targets’ section. (‘Participant’ and ‘Outcome’ annotations are removed from this file)</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.