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116 results for “cardiology”
Reducing False Arrhythmia Alarms in the ICU - The PhysioNet Computing in Cardiology Challenge 2015
<p>This dataset is part of the available dataset for <em>The PhysioNet Computing in Cardiology Challenge 2015</em>, available at https://www.physionet.org/content/challenge-2015/1.0.0/training.zip (last accessed today 2021-03-24).</p> <p>The dataset is licensed under GNU GPL license Version 3:</p> <p>Permissions:</p> <ul> <li>Commercial use</li> <li>Distribution</li> <li>Modification</li> <li>Patent use</li> <li>Private use</li> </ul> <p>Conditions:</p> <ul> <li>Disclose source</li> <li>License and copyright notice</li> <li>Same license</li> <li>State changes</li> </ul> <p>Limitations:</p> <ul> <li>Liability</li> <li>Warranty</li> </ul> <p>For more information about the license, check: https://choosealicense.com/licenses/gpl-3.0/</p> <p>The following modifications were made:</p> <ul> <li>Only the targets folder is used</li> <li>Only the files *.hea and *.mat are used, being the latter converted to CSV and compressed in .bz2 format</li> <li>Added the LICENSE.txt file as required.</li> </ul>
Geriatric CO-mAnagement for Cardiology patients in the Hospital (G-COACH): outcome data
<p>The datasets reports baseline and outcome data from the 'Geriatric CO-mAnagement for Cardiology patients in the Hospital (G-COACH)' experimental study. The study evaluated the effectiveness of a geriatric co-management programme on the cardiac care units of the University Hospitals Leuven. Sample included patients aged 75 years or older. Measurements included: demographic, functional status, cognitive status, depressive symptoms, anxiety symptoms, quality of life, physical performance, readmission rates, survival.</p> <p>Please see Word document for more information.</p> <p>Please see protocols for more information:</p> <p><a href="https://clinicaltrials.gov/ct2/show/NCT02890927">https://clinicaltrials.gov/ct2/show/NCT02890927</a></p> <p><a href="https://bmjopen.bmj.com/content/8/10/e023593">https://bmjopen.bmj.com/content/8/10/e023593</a></p> <p>The evaluation study is available at https://agsjournals.onlinelibrary.wiley.com/doi/full/10.1111/jgs.17093 </p>
Figure 4. Portal Logical Architecture-A Proposed Data Driven Architecture for Cardiology Network Application
<p>The applications that are based on a SOA environment can be configured to work both<br> as services exchanging data in point to point protocol and as a communication channel<br> between two entities that call a service provided by an entity that has the role of mediator or<br> broker. The letter can be seen as intermediary level that represents an “enterprise service bus”<br> (ESB) between service producers and consumers, offering messaging exchange services.</p>
Figure 2. System General View-A Proposed Data Driven Architecture for Cardiology Network Application
<p>Figure 2 presents a general schematic overview of the medical informational system,<br> underlying the main roles in the system together with their interactions. From an architectural<br> point of view one can identify the following main components:<br> • Host systems, named local (medical data) production systems<br> • General Practitioner system<br> • Analysis Laboratory system<br> • Hospital system<br> • Client system (interface to remote devices)<br> • Local portal (regional, national) for medical assistance, and long term data storage<br> Host systems consist of database servers connected through access points with<br> fixed/mobile medical devices. The portal will supply the functionality necessary to collect<br> information from the local interconnected systems into a centralized repository. Medical<br> services will be provided at portal level using specialized web-services that will allow access<br> to data stored in the repository.</p>
Figure 1. Schema for a data-integration solution-A Proposed Data Driven Architecture for Cardiology Network Application
<p>Data integration has favored loosening the coupling between data. This may involve<br> providing a uniform query interface over a mediated schema (see figure 1), thus transforming<br> a query into specialized queries over the original databases. One can also term this process<br> "view-based query-answering" because each of the data sources functions as a view over the<br> (nonexistent) mediated schema.</p>
Figure 3. Data Integration Sample-A Proposed Data Driven Architecture for Cardiology Network Application
<p>Pentaho Data Integration has implemented a metadata-driven approach where you<br> only specify the data you want integrated, but you do not specify the way you want it done.<br> One of the most important advantages of Pentaho is that one can create complex<br> transformations and jobs in a graphical, drag-and-drop environment without having to create<br> proprietary custom code that will work only with some proprietary application.</p>
PAVS in Cardiology
ClinicalTrials.gov study NCT04656132. IPD Sharing: YES. Countries: 1. Publications: 1.
Denoised ECGs from The PhysioNet/Computing in Cardiology Challenge 2020
<p>This dataset is a denoised version of the CPSC dataset presented in <em>Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020<sup>1</sup></em>. This dataset was used as part of the article <em>A Lightweight and Interpretable Model to classify Bundle Branch Blocks from ECG Signals.</em></p> <p>1)Perez Alday, E. A., Gu, A., Shah, A., Liu, C., Sharma, A., Seyedi, S., Bahrami Rad, A., Reyna, M., & Clifford, G. D. (2020). Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 (version 1.0.1). <em>PhysioNet</em>. <a href="https://doi.org/10.13026/f4ab-0814">https://doi.org/10.13026/f4ab-0814</a>.</p>
MultiCardioNER Corpus: Multilingual Adaptation of Clinical NER Systems to the Cardiology Domain
<h1><strong>MultiCardioNER</strong></h1> <p><strong>MultiCardioNER</strong> is a shared task about the adaptation of clinical NER systems to the cardiology domain. It uses a combination of two existing datasets (DisTEMIST for diseases and the newly-released DrugTEMIST for medications), as well as a new, smaller dataset of cardiology clinical cases annotated using the same guidelines.</p> <p>Participants are provided DisTEMIST and DrugTEMIST as training data to use as they see fit (1,000 documents, with the original partitions splitting them into 750 for training and 250 for testing). The cardiology clinical cases (cardioccc) are meant to be used as a development or validation set (258 documents), although participants are encourage to experiment with the documents and annotations as they see fit. The evaluation is done using a different collection of cardiology clinical cases (250).</p> <p>MultiCardioNER proposes two tracks:</p> <p>- Track 1: Spanish adaptation of disease recognition systems to the cardiology domain.<br>- Track 2: Multilingual (Spanish, English and Italian) adaptation of medication recognition systems to the cardiology domain.</p> <p>Please read the README file attached for more information on folder structure and file format.</p> <p><strong>MultiCardioNER</strong> was developed by the Barcelona Supercomputing Center's NLP for Biomedical Information Analysis and used as part of BioASQ 2024. For more information on the corpus, annotation scheme and task in general, please visit: <a href="https://temu.bsc.es/multicardioner" target="_blank" rel="noopener">https://temu.bsc.es/multicardioner</a>. This task is promoted by Spanish and European projects such as DataTools4Heart, AI4HF, BARITONE and AI4ProfHealth.</p> <p><strong>UPDATE MAY 28th 2024: </strong>The test set annotations are now out! We've also included the original background set files, as well as a file with the mappings from the masked filenames used during the evaluation phase to the original filenames. Please check the README for more information.</p> <h2><strong>Resources</strong></h2> <ul> <li><a href="https://temu.bsc.es/multicardioner" target="_blank" rel="noopener">MultiCardioNER website</a></li> <li><a href="http://bioasq.org/" target="_blank" rel="noopener">BioASQ website</a></li> <li><a href="../doi/10.5281/zenodo.6458078" target="_blank" rel="noopener">DisTEMIST Guidelines</a></li> <li><a href="../doi/10.5281/zenodo.11065432" target="_blank" rel="noopener">DrugTEMIST Guidelines</a></li> </ul> <h2><strong>License</strong></h2> <p>This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</p> <h2><strong>Contact</strong></h2> <p>If you have any questions or suggestions, please contact us at:</p> <p>- Salvador Lima-López (<salvador [dot] limalopez [at] gmail [dot] com>)<br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p> <h2><strong>Additional resources and corpora</strong></h2> <p>If you are interested in MultiCardioNER, you might want to check out these corpora and resources:</p> <ul> <li><a href="../records/7614764">DisTEMIST</a> (Corpus of disease mentions and normalization to SNOMED CT)</li> <li><a href="../records/8224056">MedProcNER </a>(Corpus of clinical procedure mentions and normalization to SNOMED CT)</li> <li><a href="../records/10635215">SympTEMIST</a> (Corpus of clinical findings and normalization to SNOMED CT)</li> <li><a href="../records/4270158">PharmaCoNER</a> (Corpus of medications, drugs, chemical substances, genes, proteins and vaccine mentions and normalization)</li> <li><a href="../records/7116201">MEDDOPROF</a> (Corpus of mentions of professions, occupations and working status and normalization)</li> <li><a href="../records/8403498">MEDDOPLACE</a> (Corpus of mentions of place-related entity mentions, including departments, nationalities or patient movements etc.. and normalization)</li> <li><a href="../records/4279323">MEDDOCAN</a> (Corpus of mentions of Personal Health Identifiers (PHI))</li> <li><a href="../records/3978041">CANTEMIST</a> (Corpus of cancer tumor morphology mentions and normalization)</li> <li><a href="../records/3837305">CodiESP</a> (Corpus of clinical case reportes with assigned clinical codes from ICD10, Spanish version)</li> <li><a href="../records/7684093">LivingNER</a> (Corpus of mentions of species, including human/family members, pathogens, food, etc.. and normalization to NCBI Taxonomy)</li> <li><a href="../records/2560344">SPACCC-POS</a> (Corpus of clinical case reports in Spanish annotated with POS-tags)</li> <li><a href="../records/2560338">SPACCC-TOKEN</a> (Corpus of clinical case reports in Spanish annotated with token-tags (word mention boundaries))</li> <li><a href="../records/2560338">SPACCC-SPLIT</a> (Corpus of clinical case reports in Spanish annotated with sentence boundary-tags)</li> <li><a href="../records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts)</li> </ul>
Radioprotective Light-weight Caps in the Interventional Cardiology Setting
ClinicalTrials.gov study NCT01620658. IPD Sharing: NO. Countries: 1. Publications: 1.
Communication Coaching to Improve Patient and Clinician Satisfaction in Cardiology Encounters
ClinicalTrials.gov study NCT03464110. IPD Sharing: NO. Countries: 1. Publications: 1.
Optimization of the Ambulatory Monitoring for Patients With Heart Failure by Tele-cardiology
ClinicalTrials.gov study NCT02068118. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Preoperative Cardiology Consultation and the Incidence of Major Adverse Cardiac Events（MACE）
ClinicalTrials.gov study NCT06884436. IPD Sharing: NO. Countries: 1. Publications: 3.
Predictive Monitoring - IMPact in Acute Care Cardiology Trial
ClinicalTrials.gov study NCT04359641. IPD Sharing: Not stated. Countries: 1. Publications: 2.
CardioLogical Interventions and Acute strOke Treatment sTudy
ClinicalTrials.gov study NCT07314476. IPD Sharing: NO. Countries: 1. Publications: 4.
Geriatric-CO-mAnagement for Cardiology Patients in the Hospital
ClinicalTrials.gov study NCT02890927. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
The Italian Society of Invasive Cardiology Registry on Percutaneous Aortic Valve
ClinicalTrials.gov study NCT02713932. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Virtual Reality for Preoperative Anxiety in Interventional Cardiology
ClinicalTrials.gov study NCT04242563. IPD Sharing: NO. Countries: 1. Publications: 1.
Assessment of Clinical Onset of IV Heparin in Interventional Cardiology and Cardiac Surgery
ClinicalTrials.gov study NCT04785885. IPD Sharing: NO. Countries: 1. Publications: 3.
Personal Genomics for Preventive Cardiology
ClinicalTrials.gov study NCT01406808. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.