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ShareScore release 0.9.0
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806 results for “cavities”
Next generation trophoblast organoids with apical-out trophoblast polarity and central villous core-like cavity
GEO Series GSE272513. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Expression data from cells in peritoneal cavity of CD-1 outbred mice infected with different Toxoplasma gondii strains
GEO Series GSE144854. Mus musculus; Mus musculus domesticus. 45 samples. Type: Expression profiling by array.
Dataset of Annotated Oral Cavity Images for Oral Cancer Detection
<h1>Citation</h1> <p><strong>When using this resource, please cite the original publication:</strong></p> <p><a href="https://doi.org/10.1016/j.oraloncology.2024.106946">N.S. Piyarathne, S.N. Liyanage, R.M.S.G.K. Rasnayaka, P.V.K.S. Hettiarachchi, G.A.I. Devindi, F.B.A.H. Francis, D.M.D.R. Dissanayake, R.A.N.S. Ranasinghe, M.B.D. Pavithya, I.B. Nawinne, R.G. Ragel, R.D. Jayasinghe, “A comprehensive dataset of annotated oral cavity images for diagnosis of oral cancer and oral potentially malignant disorders,” Oral Oncology, vol. 156, p. 106946, 2024</a>.</p> <p>Available at: <a href="https://doi.org/10.1016/j.oraloncology.2024.106946">https://doi.org/10.1016/j.oraloncology.2024.106946</a></p> <h1>Overview</h1> <p>The dataset consists of 3,000 high-quality images of oral cavities taken with mobile phone cameras from the Sri Lankan population. The images are categorized into healthy, benign, oral potentially malignant disorders (OPMD), and oral cancer (OCA) by domain experts. Each image contains annotations for oral cavity and lesion boundaries in COCO format. Additionally, patient metadata, such as age, sex, diagnosis, and risk factors like smoking, alcohol consumption, and betel quid chewing, is included in the meta-data files. The dataset contains the following files: </p> <ul> <li><strong>Images.zip</strong>: Folder of oral cavity images.</li> <li><strong>Annotation.json</strong>: Annotations for the images provided in the JSON (JavaScript Object Notation) file.</li> <li><strong>Imagewise_data.csv</strong>: File including the image ID, category, clinical diagnosis, and the number of annotated regions for each image.</li> <li><strong>Patientwise_data.csv</strong>: File containing patient-level metadata, including age, sex, and total image count per patient. Additionally, it includes binary indicators for risk factors such as smoking, chewing betel quid, and alcohol consumption.</li> </ul> <h1>Request Access</h1> <p>You need to satisfy these terms and conditions in order for this request to be accepted:</p> <ol> <li>Any request for access must be made through a Zenodo account associated with an official affiliation email address (e.g., institution, organization).</li> <li> <p><strong>The following details are required as the request message:</strong></p> <ul> <li>A brief description of the intended use of the dataset, outlining the purpose of their study (maximum 250 words).</li> <li> <p>Principal Investigator’s name and affiliation.</p> </li> <li> <p>Principal investigator’s page on the affiliation’s official website.</p> </li> </ul> </li> <li> <p>You may use this work <strong>only for non-commercial purposes</strong>. Any use intended for commercial gain or profit is strictly prohibited.</p> </li> <li> <p>Proper credit must be given to the creator by citing the original article associated with this dataset. </p> </li> <li> <p>No modifications, derivatives, or adaptations of this work are allowed.</p> </li> </ol> <p>Requests that adhere to the terms and conditions will be processed within 2-3 working days.</p> <h1>Authors' Publications</h1> <ol> <li> <p>A comprehensive dataset of annotated oral cavity images for diagnosis of oral cancer and oral potentially malignant disorders. DOI: <a href="https://doi.org/10.1016/j.oraloncology.2024.106946">10.1016/j.oraloncology.2024.106946</a></p> </li> <li> <p>Multimodal Deep Convolutional Neural Network Pipeline for AI-Assisted Early Detection of Oral Cancer. DOI: <a href="https://ieeexplore.ieee.org/document/10664507">10.1109/ACCESS.2024.3454338</a></p> </li> </ol>
Single photon induced instabilities in a cavity electromechanical device
Open the record for dataset details and reuse information.
Measurement of NOx and NOy with a thermal dissociation cavity ring-down spectrometer (TD-CRDS): Instrument characterisation and first deployment
<p>NOx mixing ratios measured by TD-CRDS during the 2017 AQABA ship campaign. 1 minute averages and standard deviations.</p>
Tunable nonlinear optical mapping in a multiple-scattering cavity - Data set
<p>Data set for "Tunable nonlinear optical mapping in a multiple-scattering cavity article"</p>
ScienceDex guides
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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)
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.