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342 results for “CAD”
Dataset related to the article "A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images"
<p>This record contains raw data related to the article "A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images"</p> <p>A B S T R A C T<br> Background and objective: In patients with suspected Coronary Artery Disease (CAD), the severity of stenosis needs<br> to be assessed for precise clinical management. An automatic deep learning-based algorithm to classify coronary<br> stenosis lesions according to the Coronary Artery Disease Reporting and Data System (CAD-RADS) in multiplanar<br> reconstruction images acquired with Coronary Computed Tomography Angiography (CCTA) is proposed.<br> Methods: In this retrospective study, 288 patients with suspected CAD who underwent CCTA scans were included.<br> To model long-range semantic information, which is needed to identify and classify stenosis with challenging<br> appearance, we adopted a token-mixer architecture (ConvMixer), which can learn structural relationship over<br> the whole coronary artery. ConvMixer consists of a patch embedding layer followed by repeated convolutional<br> blocks to enable the algorithm to learn long-range dependences between pixels. To visually assess ConvMixer<br> performance, Gradient-Weighted Class Activation Mapping (Grad-CAM) analysis was used.<br> Results: Experimental results using 5-fold cross-validation showed that our ConvMixer can classify significant<br> coronary artery stenosis (i.e., stenosis with luminal narrowing ≥50%) with accuracy and sensitivity of 87% and<br> 90%, respectively. For CAD-RADS 0 vs. 1–2 vs. 3–4 vs. 5 classification, ConvMixer achieved accuracy and<br> sensitivity of 72% and 75%, respectively. Additional experiments showed that ConvMixer achieved a better<br> trade-off between performance and complexity compared to pyramid-shaped convolutional neural networks.<br> Conclusions: Our algorithm might provide clinicians</p>
CAD-C reveals the near-perfect alignment of sister chromatids
GEO Series GSE312896. Saccharomyces cerevisiae. 6 samples. Type: Other.
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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.
Annotated Behaviour and Observability Dataset (ABODe)
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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.