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238
datasets available to search
ShareScore release 0.9.0
Dataset results
238 results for “Radiomics;”
Radiomics in Pancreatic Cancer
ClinicalTrials.gov study NCT05658679. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Data from: Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study
Open the record for dataset details and reuse information.
Data from: 18F-fluorodeoxyglucose positron-emission tomography (FDG-PET)-Radiomics of metastatic lymph nodes and primary tumor in non-small cell lung cancer (NSCLC) – A prospective externally validated study
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Heterogenous radiomics patterns are associated with poor survivals and dysregulated pathways in medulloblastoma
GEO Series GSE151519. Homo sapiens. 17 samples. Type: Expression profiling by high throughput sequencing.
Multimodal integration of transcriptomics, proteomics and radiomics improves prediction of recurrence in patients with IDH-mutant Glioma
GEO Series GSE226321. Homo sapiens. 59 samples. Type: Expression profiling by high throughput sequencing.
Radiomics Predicts High or Low Recurrence Risk and is Associated with LncRNAs in Breast Cancer
GEO Series GSE189371. Homo sapiens. 96 samples. Type: Expression profiling by high throughput sequencing.
Radiomic and gEnomic approaches for the enhanced DIagnosis of REnal Cancer (REDIRECt): A translational pilot study
GEO Series GSE133460. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"
<p><strong>Abstract</strong></p><p> </p><p><strong>Background</strong></p><p> </p><p>In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor.</p><p> </p><p><strong>Methods</strong></p><p> </p><p>112 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images.</p><p> </p><p><strong>Findings</strong></p><p> </p><p>From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%).</p><p>Upon cross-validation, ComBat algorithm obtained a mean R2 higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R2 in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat.</p><p> </p><p> </p><p><strong>Interpretation</strong></p><p> </p><p>This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.</p>
Radiomic Features for Breast Cancer Outcome Prediction
<p>The dataset was curated for investigating breast cancer clinical outcome prediction. In this setting, radiomics features from baseline dynamic contrast-enhanced MRI (DCE-MRI) of 466 breast cancer patients were extracted.</p>
Pancreatic cancer detection and characterization: state of the art and radiomics.
<p>We uploaded the images of the manuscript: Granata V, Grassi R, Fusco R, Galdiero R, Setola SV, Palaia R, Belli A, Silvestro L, Cozzi D, Brunese L, Petrillo A, Izzo F. Pancreatic cancer detection and characterization: state of the art and radiomics. Eur Rev Med Pharmacol Sci. 2021 May;25(10):3684-3699. doi: 10.26355/eurrev_202105_25935. PMID: 34109578.</p>
Application of Radiomics in Precise Preoperative Diagnosis and Prognsis Evaluation of Colorectal Cancer.
ClinicalTrials.gov study NCT03787667. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of the Use of a Method "Radiomics" for DOPA PET in Gliomas
ClinicalTrials.gov study NCT06472440. IPD Sharing: Not stated. Countries: 1. Publications: 0.
By Developing a Radiomics Model to Predict the Prognosis of Patients With Hepatocellular Carcinoma After Microwave Ablation
ClinicalTrials.gov study NCT03880721. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Noninvasive Evaluation of Fetal Hyperinsulinemia With Ultrasound Radiomics
ClinicalTrials.gov study NCT06343974. IPD Sharing: NO. Countries: 1. Publications: 0.
CADx - Radiomics to Distinguish the Origin of Ovarian Tumors
ClinicalTrials.gov study NCT05174377. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Establishment of Radiomics Database by Clinical Application of Multiparametric MRI Based on Incoherent Undersampling
ClinicalTrials.gov study NCT02944006. IPD Sharing: NO. Countries: 1. Publications: 0.
CT-based Radiomic Algorithm for Assisting Surgery Decision and Predicting Immunotherapy Response of NSCLC
ClinicalTrials.gov study NCT04452058. IPD Sharing: NO. Countries: 1. Publications: 0.
Radiomic Assessment in NSCLC: Correlation Between Multiparametric Imaging Biomarkers and Genetic Biomarkers
ClinicalTrials.gov study NCT01585545. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Radiomics of Immunotherapeutics Response Evaluation and Prediction
ClinicalTrials.gov study NCT04079283. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Study Using Genomic, Histologic and Radiomic Analysis to Evaluate Regional Tumor Heterogeneity in Patients Undergoing Surgery for Newly Diagnosed Glioblastoma
ClinicalTrials.gov study NCT03287063. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
ScienceDex guides
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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.