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1,201
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Dataset results
1,201 results for “Oncology”
Implementation of a Rapid Recovery Program in Gynecologic Oncology Surgery: A Pilot Study
ClinicalTrials.gov study NCT01705288. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Community-Based Exercise Oncology: Real-World Evidence of High Adherence, Improved Quality of Life and Cost-Effectiveness Across the Cancer Continuum
ClinicalTrials.gov study NCT07368192. IPD Sharing: NO. Countries: 1. Publications: 1.
TXA Study in Major Oncologic Surgery
ClinicalTrials.gov study NCT01980355. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Natural History With Focus on Oncological Risk Evaluation in Pediatric Patients With PTEN Pathogenic Variants - Observational Study
ClinicalTrials.gov study NCT06805734. IPD Sharing: YES. Countries: 1. Publications: 3.
Supportive Oncology Care at Home for Patients With Pancreatic Cancer Receiving Preoperative FOLFIRINOX
ClinicalTrials.gov study NCT03798769. IPD Sharing: YES. Countries: 1. Publications: 1.
Implementation of Smoking Cessation Within NCI Community Oncology Research Program (NCORP) Sites
ClinicalTrials.gov study NCT03291587. IPD Sharing: YES. Countries: 1. Publications: 47.
Erlotinib vs. Standard Chemotherapy in Patients With Advanced Non-small Cell Lung Cancer (NSCLC) and Eastern Cooperative Oncology Group (ECOG)Performance Status (PS) 2
ClinicalTrials.gov study NCT00085839. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Geriatric Oncology Care in Brazil: Remote Geriatric Assessment-Driven Interventions With Supportive Care
ClinicalTrials.gov study NCT07084454. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
Fast-track Surgery After Gynecological Oncology Surgery
ClinicalTrials.gov study NCT02687412. IPD Sharing: NO. Countries: 1. Publications: 24.
Initial Testing of a Mobile App Pain Coping Intervention for Outpatient Oncology Settings (PainPac)
ClinicalTrials.gov study NCT05686122. IPD Sharing: NO. Countries: 1. Publications: 0.
Medical publications with information as to whether a publication reports a randomized controlled trial and/or if it covers an oncology topic
Open the record for dataset details and reuse information.
15-gene expression profile and PRAME as an integrated prognostic test for uveal melanoma: First report of Collaborative Ocular Oncology Group Study No. 2 (COOG2.1)
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Behavioural ecology meets oncology: quantifying the recovery of animal behaviour to a transient exposure to a cancer risk factor
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Cantemist corpus: gold standard of oncology clinical cases annotated with CIE-O 3 terminology
<p><strong>Intro:</strong></p> <p>Cantemist shared task dataset (divided in train, dev1, dev2 and test). In addition, we include here the Cantemist background set.</p> <p>It contains the train, development and test sets of the three subtasks: cantemist-ner, cantemist-norm and cantemist-coding with Gold Standard annotations.</p> <p>In addition, it contains the documents of the background set, without annotations.</p> <p> </p> <p><strong>Please cite if you use this dataset:</strong></p> <p>Miranda-Escalada, A., Farré, E., & Krallinger, M. (2020). Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results. In <em>Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings</em>.</p> <pre><code>@inproceedings{miranda2020named, title={Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results}, author={Miranda-Escalada, A and Farr{\'e}, E and Krallinger, M}, booktitle={Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings}, year={2020} }</code></pre> <p> </p> <p><strong>Format:</strong></p> <p>For subtasks cantemist-norm and cantemist-ner, annotations are distributed in Brat format. See <a href="https://brat.nlplab.org/standoff.html">Brat webpage</a> for more information</p> <p>For subtask cantemist-coding, codes are grouped in a TSV file with the following columns (this follows the format used in <a href="https://temu.bsc.es/codiesp/">CodiEsp shared task</a>): </p> <blockquote> <p>filename code</p> </blockquote> <p> </p> <p><strong>Shared task goal:</strong></p> <p>In the three subtasks, the goal will be to predict the annotations (either the ANN files or the TSV with the codes) given only the plain text files. </p> <p> </p> <p><strong>Resources:</strong></p> <ul> <li><strong><a href="https://temu.bsc.es/cantemist/">Web</a></strong></li> <li><strong><a href="http://ceur-ws.org/Vol-2664/cantemist_overview.pdf">Citation</a>: </strong>Miranda-Escalada, A., Farré, E., & Krallinger, M. (2020). Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results. In <em>Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings</em>.</li> <li><strong><a href="https://doi.org/10.5281/zenodo.4010899">Silver Standard corpus</a></strong></li> <li><strong><a href="https://doi.org/10.5281/zenodo.3878178">Annotation guidelines</a></strong></li> <li><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhC24g5dsp5eVMp8BZFWCraX"><strong>YouTube presentations</strong></a></li> <li><a href="https://temu.bsc.es/cantemist/?p=4606"><strong>Participant codes</strong></a></li> </ul> <p> </p> <p>For further information, please visit <a href="https://temu.bsc.es/cantemist/">https://temu.bsc.es/cantemist/</a> or email us at encargo-pln-life@bsc.es</p>
Cantemist Silver Standard: Participant predictions in SEPLN IberLEF2020 - Spanish oncology clinical cases coded in ICD-O
<p><strong>Introduction</strong></p> <p>Predictions in the background set of Cantemist participants.</p> <p> </p> <p><strong>Zip structure</strong></p> <p>One directory per Cantemist subtask. Within each Cantemist subtask directory, there is one directory per team that contains the prediction runs.</p> <p> </p> <p><strong>Format</strong></p> <p>The text documents are distributed in plain text files, UTF-8 encoding.<br> The CodiEsp Silver Standard annotations have the following format:</p> <p>For the sub-tracks Cantemist-NER and Cantemist-Norm, the files are in Brat format.</p> <p>For the sub-track Cantemist-Coding files have the following fields:</p> <pre>articleID ICDO-code </pre> <p> </p> <p><strong>Resources:</strong></p> <ul> <li><strong><a href="https://temu.bsc.es/cantemist/">Web</a></strong></li> <li><strong>Citation: </strong>Miranda-Escalada, A., Farré, E., & Krallinger, M. (2020). Named entity recognition, concept normalization and clinical coding: Overview of the cantemist track for cancer text mining in spanish, corpus, guidelines, methods and results. In <em>Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020), CEUR Workshop Proceedings</em>.</li> <li><a href="https://doi.org/10.5281/zenodo.3773228"><strong>Gold Standard corpus</strong></a></li> <li><strong><a href="https://doi.org/10.5281/zenodo.3878178">Annotation guidelines</a></strong></li> <li><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhC24g5dsp5eVMp8BZFWCraX"><strong>YouTube presentations</strong></a></li> <li><a href="https://temu.bsc.es/cantemist/?p=4606"><strong>Participant codes</strong></a></li> </ul> <p> </p> <p>All credit to Cantemist participants. </p> <p> </p> <p>For more information, visit the track webpage: <a href="http://temu.bsc.es/cantemist/">http://temu.bsc.es/cantemist/</a> or email us at encargo-pln-life@bsc.es</p>
Genomic profiling of NSCLC tumors with the TruSight Oncology 500 assay provides broad coverage of clinically actionable genomic alterations and detection of known and novel associations between genomic alterations, TMB, and PD-L1
<p>Wallen ZD, Ko H, Nesline MK, Tierno M, Roos A, Schnettler E, Husain H, Sathyan P, Caveney B, Eisenberg M, Severson EA, Ramkissoon SH. <strong>Genomic profiling of NSCLC tumors with the TruSight Oncology 500 assay provides broad coverage of clinically actionable genomic alterations and detection of known and novel associations between genomic.</strong> <em>Front Oncol.</em> 2024 Nov 5;14:1473327. doi: <a href="https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1473327">10.3389/fonc.2024.1473327</a>.</p> <p><strong>ABSTRACT</strong></p> <p><strong>Introduction: </strong>Matching patients to an effective targeted therapy or immunotherapy is a challenge for <br>advanced and metastatic non-small cell lung cancer (NSCLC), especially when relying on assays that test one <br>marker at a time. Unlike traditional single marker tests, comprehensive genomic profiling (CGP) can <br>simultaneously assess NSCLC tumors for hundreds of genomic biomarkers and markers for immunotherapy <br>response, leading to quicker and more precise matches to therapeutics. <strong>Methods: </strong>In this study, we performed <br>CGP on 7,606 patients with advanced or metastatic NSCLC using the Illumina TruSight Oncology 500 (TSO <br>500) CGP assay to show its coverage and utility in detecting known and novel features of NSCLC. <strong>Results: </strong><br>Testing revealed distinct genomic profiles of lung adenocarcinoma and squamous cell carcinomas and <br>detected variants with a current targeted therapy or clinical trial in >72% of patient tumors. Known associations <br>between genomic alterations and immunotherapy markers were observed including significantly lower TMB <br>levels in tumors with therapy-associated alterations and significantly higher PD-L1 levels in tumors with ALK, <br>MET, BRAF, or ROS1 driver mutations. Co-occurrence analysis followed by network analysis with gene <br>module detection revealed known and novel co-occurrences between genomic alterations. Further, certain <br>modules of genes with co-occurring genomic alterations had dose-dependent relationships with histology and <br>increasing or decreasing levels of PD-L1 and TMB, suggesting a complex relationship between PD-L1, TMB, <br>and genomic alterations in these gene modules. <strong>Discussion:</strong> This study is the largest clinical study to date <br>utilizing the TSO 500. It provides an opportunity to further characterize the landscape of NSCLC using this <br>newer technology and show its clinical utility in detecting known and novel facets of NSCLC to inform treatment <br>decision-making.</p> <p><strong>DATA AVAILABILITY</strong></p> <p>The data and code presented in the study are deposited in this Zenodo repository, accession number <br>13137232 (<a href="https://zenodo.org/record/13137232">https://zenodo.org/record/13137232</a>). Raw sequencing data were derived from routine clinical testing of real-world patients and cannot be shared publicly. Further data inquiries can be directed to the corresponding <br>author. </p>
Affordable prices without threatening the oncological R&D pipeline - An economic experiment on transparency in price negotiations
<p>This is the data repository of an economic experiment on the effects of transparency regulations, conducted by the Netherlands Cancer Institute and the University of Amsterdam. We replicated the EU pharmaceutical market in a laboratory setting. In a randomized-controlled study, we analyzed how participants, 400 students located in 4 European countries, negotiated in the current system of Price Secrecy in comparison to innovative bargaining settings where either prices only (Price Transparency) or prices and R&D costs (Full Transparency) were made transparent to buyers.</p>
Digital health monitoring and digital endpoints in oncology
<p>Raw data set from GLOBOCAN and www.clinicaltrials.gov used for thesis work of "<strong>Digital health monitoring and digital endpoints in oncology</strong>"</p>
Pulmonary lymphangitis pose a major challenge for radiologists in an oncological setting during the COVID-19 pandemic
<p>I uploaded the images of the manuscript "Pulmonary lymphangitis pose a major challenge for radioLogists in an oncological setting during the COVID-19 pandemic".</p>
GERDAT013 Dataset for literature search linked to publication "Patient Preferences for Treatment Outcomes in Oncology with a Focus on the Older Patient—A Systematic Review"
<p>Dataset of the literature search belonging to the publication "Patient preferences for treatment outcomes in oncology with a focus on the older patient- a systematic review."</p>
ScienceDex guides
Understand access before you commit
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.