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Dataset results
342 results for “CAD”
Data Collection for CAD Evaluation
ClinicalTrials.gov study NCT01600144. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Patient Satisfaction of Glazed IPS Empress CAD Versus Glazed Celtra Duo Ceramic Laminate Veneers
ClinicalTrials.gov study NCT03129711. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Understanding the Effect of Metformin on Corus CAD (or ASGES)
ClinicalTrials.gov study NCT02440893. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Antithrombotic Strategy for AF Patients With High Risk CAD
ClinicalTrials.gov study NCT06866665. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Optima Coronary Artery Disease (CAD) (Optimal Mechanical Evaluation)
ClinicalTrials.gov study NCT00896142. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Kor PCI - CAD Patients Treated With PCI: Analysis of the Korean Nationwide Health Insurance Database
ClinicalTrials.gov study NCT04778969. IPD Sharing: NO. Countries: 0. Publications: 0.
Shade Match, Marginal Adaptation and Patient Satisfaction of VITA ENAMIC multiColor Versus IPS e.Max CAD Veneers
ClinicalTrials.gov study NCT04774614. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Repository of Phase Signals for Algorithm Development and Testing in CAD in CHINA
ClinicalTrials.gov study NCT04034537. IPD Sharing: NO. Countries: 0. Publications: 0.
Physical Exercise Versus Rosiglitazone in CAD and Prediabetes
ClinicalTrials.gov study NCT00675740. IPD Sharing: Not stated. Countries: 0. Publications: 0.
One Year Clinical Evaluation of IPS Empress CAD Versus Polished Celtra Duo Ceramic Laminate Veneers
ClinicalTrials.gov study NCT03136276. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
PGE1 Improves Coronary Microcirculation Dysfunction in Patients With CAD and Diabetes
ClinicalTrials.gov study NCT03159559. IPD Sharing: Not stated. Countries: 0. Publications: 0.
GE/miRNA expression profile of Human Epicardial Adipose Tissue (EAT) and Subcutaneous Adipose Tissue (SAT) in Patients with Coronary Artery Disease (CAD) vs. Controls (CTRL)
GEO Series GSE64566. Homo sapiens. 92 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
Gene expression changes in galls at 21 dai and corresponding uninfected roots from Poplar CAD and WT lines
GEO Series GSE112673. Populus tremula x Populus alba. 11 samples. Type: Expression profiling by high throughput sequencing.
RNA sequencing and small RNA sequencing in WT and mir-138 DKO CAD cell lines
GEO Series GSE125853. Mus musculus. 34 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Pyrimidine synthase CAD deamidates and inactivates p53
GEO Series GSE286372. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Parametric CAD models reconstruction from B-Rep models
<p>This dataset is built to construct 3D parametric CAD models from B-Rep models (step files) and is based on the public datasets ABC and DeepCAD. The original B-Rep models are from ABC, and the corresponding CAD command sequences are from DeepCAD. In addition, the dataset contains two parts that are B-Rep models and CAD command sequences. Here, the B-Rep models are converted to UV-graphs (folder '/uv_graph'); the command sequences are in folder '/cad_vec'.</p>
HybridCAD: A Comprehensive Dataset for Hybrid Additive-Subtractive Manufacturing Feature Recognition in B-Rep CAD Models
<p>The <em>HybridCAD</em> dataset is a novel resource tailored for hybrid additive-subtractive feature recognition in Computer-Aided Design (CAD) models, uniquely combining features from both manufacturing processes. Building on the <em>MFCAD</em> and <em>MFCAD++</em> datasets, <em>HybridCAD</em> introduces additive manufacturing features alongside traditional subtractive ones, enabling the exploration and development of machine learning models for more complex, hybrid manufacturing applications. This dataset is especially suited for automatic feature recognition (AFR) research and model training in hybrid manufacturing contexts.</p> <h3>Dataset Composition</h3> <p>The dataset consists of 8,938 Boundary Representation (B-Rep) CAD models distributed into three main directories:</p> <ol> <li> <p><strong>STEP Files</strong>:</p> <ul> <li>Contains CAD models in STEP format, each representing a distinct part with hybrid manufacturing features.</li> <li>Generated using PythonOCC CAD software, these CAD files serve as the foundation for feature recognition tasks.</li> </ul> </li> <li> <p><strong>Feature Labels</strong>:</p> <ul> <li><strong>File</strong>: <code>feature_labels.txt</code></li> <li>Provides unique label IDs for each B-Rep face in every CAD model, denoting the manufacturing feature name it belongs to.</li> <li>Each CAD model face is labelled according to one of 29 hybrid additive-subtractive features, allowing for accurate and detailed feature recognition.</li> </ul> <ul> <li> </li> </ul> </li> <li> <p><strong>Hierarchical B-Rep Graphs</strong>:</p> <ul> <li>Stored in HDF5 format for structured access to B-Rep data.</li> <li>Detailed structural information is available in <code>h5_structure.txt</code>, explaining the hierarchical arrangement of B-Rep graphs.</li> </ul> </li> </ol> <h3>Dataset Splits</h3> <p>The dataset is split into training, validation, and testing sets as follows:</p> <ul> <li><strong>Training Set</strong>: 6,256 samples (70%)</li> <li><strong>Validation Set</strong>: 1,342 samples (15%)</li> <li><strong>Testing Set</strong>: 1,340 samples (15%)</li> </ul> <h3>Hybrid Manufacturing Features</h3> <p><em>HybridCAD</em> includes a diverse range of additive and subtractive manufacturing features, expanding beyond the subtractive-only features of <em>MFCAD++</em>. This inclusion enables the exploration of hybrid manufacturing processes and the recognition of a broader feature set in CAD models. The complete feature list includes:</p> <p>Label Feature<br>0 Chamfer<br>1 Through hole<br>2 Triangular passage<br>3 Rectangular passage<br>4 6-sided passage<br>5 Triangular through slot<br>6 Rectangular through slot<br>7 Circular through slot<br>8 Rectangular through step<br>9 2-sided through step<br>10 Slanted through step<br>11 O-ring<br>12 Blind hole<br>13 Triangular pocket<br>14 Rectangular pocket<br>15 6-sided pocket<br>16 Circular end pocket<br>17 Rectangular blind slot<br>18 Vertical circular end blind slot<br>19 Horizontal circular end blind slot<br>20 Triangular blind step<br>21 Circular blind step<br>22 Rectangular blind step<br>23 Round<br>24 Extrude cylinder<br>25 Extrude rectangle<br>26 Extrude triangle<br>27 Extrude hexagon<br>28 Extrude pentagon<br>29 Stock</p>
affy_rnai_cadpoplars: Transcriptome analysis of RNAi-CAD transgenic poplars
GEO Series GSE27063. Populus tremula x Populus alba; Populus sp.. 4 samples. Type: Expression profiling by array.
Dataset related to the article: "CT Perfusion Versus Coronary CT Angiography in Patients With Suspected In-Stent Restenosis or CAD Progression"
<p>This record contains raw data related to the article "CT Perfusion Versus Coronary CT</p> <p>Angiography in Patients With Suspected</p> <p>In-Stent Restenosis or CAD Progression"</p> <p>OBJECTIVES The goal of this study was to assess the diagnostic performance of coronary computed tomography</p> <p>angiography (CTA) alone, adenosine-stress myocardial perfusion assessed by computed tomography (CTP) alone, and</p> <p>coronary CTA þ CTP by using a 16-cm Z-axis coverage scanner versus invasive coronary angiography (ICA) and fractional</p> <p>flow reserve (FFR) as the clinical standard.</p> <p>BACKGROUND Diagnostic performance of coronary CTA for in-stent restenosis detection is still challenging. Recently,</p> <p>CTP showed additional diagnostic power over coronary CTA in patients with suspected coronary artery disease. However,</p> <p>few data are available on CTP performance in patients with previous stent implantation.</p> <p>METHODS Consecutive stable patients with previous coronary stenting referred for ICA were enrolled. All patients</p> <p>underwent stress myocardial CTP and rest CTP þ coronary CTA. Invasive FFR was performed during ICA when clinically</p> <p>indicated. The diagnostic rate and diagnostic accuracy of coronary CTA, CTP, and coronary CTA þ CTP were evaluated in</p> <p>stent-, territory-, and patient-based analyses.</p> <p>RESULTS In the 150 enrolled patients (132 men; mean age 65.1 9.1 years), the CTP diagnostic rate was significantly</p> <p>higher than that of coronary CTA in all analyses (territory based [96.7% vs. 91.1%; p < 0.0001] and patient based [96%</p> <p>vs. 68%; p < 0.0001]). When ICA was used as gold standard, CTP diagnostic accuracy was significantly higher than that</p> <p>of coronary CTA in all analyses (territory based [92.1% vs. 85.5%, p < 0.03] and patient based [86.7% vs. 76.7%,</p> <p>p < 0.03]). The concordant coronary CTA þ CTP assessment exhibited the highest diagnostic accuracy values versus ICA</p> <p>(95.8%in the territory-based analysis). The diagnostic accuracy of CTP was significantly higher than that of coronary CTA</p> <p>(75% vs. 30.5%; p < 0.001). The radiation exposure of coronary CTA þ CTP was 4.15 1.5 mSv.</p> <p>CONCLUSIONS In patients with coronary stents, CTP significantly improved the diagnostic rate and accuracy of coronary</p> <p>CTA alone compared with both ICA and invasive FFR as gold standard.</p>
Subcutaneous, Paracardiac, and Epicardial Fat CT Density Before/After Contrast Injection: Any Correlation with CAD?
<p>Dataset from Monti CB, Capra D, Malavazos A, Florini G, Parietti C, Schiaffino S, Sardanelli F, Secchi F. Subcutaneous, Paracardiac, and Epicardial Fat CT Density Before/After Contrast Injection: Any Correlation with CAD? J Clin Med. 2021 Feb 12;10(4):735. doi: 10.3390/jcm10040735. PMID: 33673256; PMCID: PMC7918165.</p> <p>Abstract</p> <p>Adipose tissue, in particular epicardial adipose tissue, has been identified as a potential biomarker of cardiovascular pathologies such as coronary artery disease (CAD) in the light of its metabolic activity and close anatomic and pathophysiologic relationship to the heart. Our purpose was to evaluate epicardial adipose tissue density at both unenhanced and contrast-enhanced computed tomography (CT), along with CT densities of paracardiac and subcutaneous adipose tissue, as well as the relations of such densities with CAD. We retrospectively reviewed patients who underwent cardiac CT at our institution for CAD assessment. We segmented regions of interest on epicardial, paracardiac, and subcutaneous adipose tissue on unenhanced and contrast-enhanced scans. A total of 480 patients were included, 164 of them presenting with CAD. Median epicardial adipose tissue density measured on contrast-enhanced scans (-81.5 HU; interquartile range -84.9 to -78.0) was higher than that measured on unenhanced scans (-73.4 HU; -76.9 to -69.4) (<em>p</em> < 0.001), whereas paracardiac and subcutaneous adipose tissue densities were not (<em>p</em> ≥ 0.055). Patients with or without CAD, did not show significant differences in density of epicardial, paracardiac, and subcutaneous adipose tissue either on unenhanced or contrast-enhanced scans (<em>p</em> ≥ 0.092). CAD patients may experience different phenomena (inflammation, fibrosis, increase in adipose depots) leading to rises or drops in epicardial adipose tissue density, resulting in variations that are difficult to detect.</p>
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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.