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Dataset results

37 results for “Automated Software”

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dryad32/100

Data from: Animal Sound Identifier (ASI): software for automated identification of vocal animals

Open the record for dataset details and reuse information.

publicMay 2019View details →
zenodo28/100

Data from "SynBot: An open-source image analysis software for automated quantification of synapses"

<p>Primary image datasets and associated tables from the paper "SynBot: An open-source image analysis software for automated quantification of synapses".&nbsp;</p>

opencc-by-4.0Jun 2024View details →
zenodo28/100

Dataset of bugs in automated driving softwares

Open the record for dataset details and reuse information.

opencc-by-4.0Aug 2024View details →
zenodo28/100

Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects

<p>This is the dataset for the publication &quot;Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects&quot;.</p> <p>It contains just-in-time defect-prediction style data in jit_data2.tar.gz as well as warnings generated by PMD 6.31.0 in warnings_data3.tar.gz.</p> <p>Further information and scripts for generating the plots and tables can be found in the <a href="https://github.com/atrautsch/emse2021a_replication">replication kit</a>.</p>

openother-openOct 2022View details →
ClinicalTrials.gov28/100

Efficacy and Safety of AEYE-DS Software Device for Automated Detection of Diabetic Retinopathy From Digital Fundus Images

ClinicalTrials.gov study NCT04612868. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo24/100

[Dataset] Minecraft: Automated Mining of Software Bug Fixes with Precise Code Context

<p>Repository mining of bug fixes from version control systems like GitHub is a challenging problem as far as the precision of the bug context is concerned before and after the fix. Coupled with this, identification of the type of the bug fix goes a long way towards creating high quality datasets that can be used for several downstream tasks. However, existing bug fix datasets suffer from the following limitations that dilute the data quality. Firstly, they do not focus on multilingual projects in their entirety given that most open-source projects are now multilingual. Secondly, the granularity of the bug fixes are considered only at the function/method level without specifying line/statement level information. Thirdly, bug fixes lying within the scope of a source file but outside any of its constituent functions have not been examined. In this paper, we propose a solution to overcome the aforementioned limitations by introducing a novel and extensive dataset named Minecraft. With a size of 28.8GB (considering 416 GitHub projects encompassing programming languages such as C, C++, Java, and Python, 2.2M commits, 3.29M bug-fix pairs), Minecraft surpasses the existing datasets by 4-fold enlargement in terms of data availability. We believe Minecraft would serve as a valuable resource for various stakeholders in the software development and research communities, empowering them to improve software quality, develop innovative bug detection and auto-fix techniques, and<br> advance the field of software engineering.<br> &nbsp;</p>

opencc-by-4.0Jul 2023View details →
ClinicalTrials.gov24/100

Evaluation of a Novel Non-Invasive Automated Fractional Flow Reserve Software System in Patients With Coronary Artery Disease

ClinicalTrials.gov study NCT06183294. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Accuracy of the LiverVision® Semi-automated Liver Volumetry Software

ClinicalTrials.gov study NCT03766633. IPD Sharing: NO. Countries: 3. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Efficacy and Safety of AEYE-DS Software Device for Automated Detection of Diabetic Retinopathy From Digital Funduscopic Images

ClinicalTrials.gov study NCT05857943. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Validation and Feasibility in Clinical Practice and Concordance of an Automated System Coupling an RGB-D Camera and a Software Based on Artificial Intelligence for the Measurement of Shoulder Range of

ClinicalTrials.gov study NCT05292157. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

UK Validation of the Automated "AcceXible" Speech Analysis Software

ClinicalTrials.gov study NCT05534958. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo20/100

Pharmacological validation of the pre-pulse inhibition of startle response in larval zebrafish using a commercial automated system and software

<p>Measurements for plexiglass custom made plate</p>

opencc-by-4.0Apr 2020View details →
ClinicalTrials.gov20/100

Implementation and Validation of Telemedicine Software for the Automation of MRI Examinations of Acute Myocardial Infarctions

ClinicalTrials.gov study NCT03601481. IPD Sharing: Not stated. Countries: 0. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo12/100

Dataset related to the article "Feasibility and Accuracy of the Automated Software for Dynamic Quantification of Left Ventricular and Atrial Volumes and Function in a Large Unselected Population"

<p>This record contains raw data related to the article &ldquo;Feasibility and Accuracy of the Automated Software for Dynamic Quantification of Left Ventricular and Atrial Volumes and Function in a Large Unselected Population&rdquo;</p> <p>Abstract</p> <p>We aimed to evaluate the feasibility and accuracy of machine learning-based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes in an unselected population. We enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV, and LA volumes were obtained from 2D images; 3D images were analyzed using dynamic heart model (DHM) software (Philips) resulting in LV and LA volume-time curves. A subgroup of 140 patients also underwent cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded, and results were compared between 2DTTE, DHM, and CMR. The use of DHM was feasible in 522/600 cases (87%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n = 38) or minor (n = 149) border corrections were needed. The overall time required for DHM datasets was approximately 40 seconds. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173 &plusmn; 64 vs. 142 &plusmn; 58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55% &plusmn; 12 vs. 56% &plusmn; 14; LA volume 89 &plusmn; 36 vs. 89 &plusmn; 38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r = 0.70 and r = 0.82,&nbsp;<em>p</em>&nbsp;&lt; 0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r = 0.82,&nbsp;<em>p</em>&nbsp;&lt; 0.001) and LA volumes. The DHM software is feasible, accurate, and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation.</p>

restrictedJan 2022View details →
zenodo12/100

Supplementary Material - Dataset for "Automating Quantum Software Maintenance: Flakiness Detection and Root Cause Analysis"

Open the record for dataset details and reuse information.

restrictedcc-by-4.0Oct 2024View details →
zenodo12/100

Pre-TAVI aortic annulus sizing: Comparison between manual and semi-automated new generation software measurements in operators with different experience

<p>The study compares manual and semi-automatic measurements (with specific dedicated GE Software)&nbsp;for aortic annulus assessment among different operators with different experience</p>

restrictedJul 2023View details →
zenodo8/100

Master thesis: Evaluating Contemporary Approaches for Automated Compliance Checks of Software-intensive Systems

<p>The dataset and code used in and generated during the master thesis, from raw data over analysis artifacts to the research outcomes.</p>

restrictedJul 2023View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record