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dc.contributor.authorAlzate-Grisales, Jesús Alejandro
dc.contributor.authorMora-Rubio, Alejandro
dc.contributor.authorArteaga-Arteaga, Harold Brayan
dc.contributor.authorBravo-Ortiz, Mario Alejandro
dc.contributor.authorArias-Garzón, Daniel
dc.contributor.authorLópez-Murillo, Luis Humberto
dc.contributor.authorMercado-Ruiz, Esteban
dc.contributor.authorVilla-Pulgarin, Juan Pablo
dc.contributor.authorCardona-Morales, Oscar
dc.contributor.authorOrozco-Arias, Simon
dc.contributor.authorBuitrago-Carmona, Felipe
dc.contributor.authorPalancares-Sosa, Maria Jose
dc.contributor.authorMartínez-Rodríguez, Fernanda
dc.contributor.authorContreras-Ortiz, Sonia H.
dc.contributor.authorSaborit-Torres, Jose Manuel
dc.contributor.authorMontell Serrano, Joaquim Ángel
dc.contributor.authorRamirez-Sánchez, María Mónica
dc.contributor.authorSierra-Gaber, ario Alfonso
dc.contributor.authorJaramillo-Robled, Oscar
dc.contributor.authorde la Iglesia-Vayá, Maria
dc.contributor.authorTabares-Soto, Reinel
dc.date.accessioned2023-07-21T16:24:12Z
dc.date.available2023-07-21T16:24:12Z
dc.date.issued2022
dc.date.submitted2023
dc.identifier.citationAlzate-Grisales, J. A., Mora-Rubio, A., Arteaga-Arteaga, H. B., Bravo-Ortiz, M. A., Arias-Garzón, D., López-Murillo, L. H., ... & Tabares-Soto, R. (2022). Cov-caldas: A new COVID-19 chest X-Ray dataset from state of Caldas-Colombia. Scientific Data, 9(1), 757.spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/12339
dc.description.abstractThe emergence of COVID-19 as a global pandemic forced researchers worldwide in various disciplines to investigate and propose efficient strategies and/or technologies to prevent COVID-19 from further spreading. One of the main challenges to be overcome is the fast and efficient detection of COVID-19 using deep learning approaches and medical images such as Chest Computed Tomography (CT) and Chest X-ray images. In order to contribute to this challenge, a new dataset was collected in collaboration with “S.E.S Hospital Universitario de Caldas” (https://hospitaldecaldas.com/) from Colombia and organized following the Medical Imaging Data Structure (MIDS) format. The dataset contains 7,307 chest X-ray images divided into 3,077 and 4,230 COVID-19 positive and negative images. Images were subjected to a selection and anonymization process to allow the scientific community to use them freely. Finally, different convolutional neural networks were used to perform technical validation. This dataset contributes to the scientific community by tackling significant limitations regarding data quality and availability for the detection of COVID-19. © 2022, The Author(s).spa
dc.format.extent10 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceScientific Data, 9(1)spa
dc.titleCov-caldas: A new COVID-19 chest X-Ray dataset from state of Caldas-Colombiaspa
dcterms.bibliographicCitationWang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., (...), Peng, Z. Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China (2020) JAMA - Journal of the American Medical Association, 323 (11), pp. 1061-1069. Cited 15066 times. http://jama.jamanetwork.com/journal.aspx doi: 10.1001/jama.2020.1585spa
dcterms.bibliographicCitationAnis, S., Lai, K.W., Chuah, J.H., Ali, S.M., Mohafez, H., Hadizadeh, M., Yan, D., (...), Ong, Z.-C. An overview of deep learning approaches in chest radiograph (2020) IEEE Access, 8, pp. 182347-182354. Cited 18 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 doi: 10.1109/ACCESS.2020.3028390spa
dcterms.bibliographicCitationOhata, E.F., Bezerra, G.M., Chagas, J.V.S.D., Lira Neto, A.V., Albuquerque, A.B., Albuquerque, V.H.C.D., Reboucas Filho, P.P. Automatic detection of COVID-19 infection using chest X-ray images through transfer learning (2021) IEEE/CAA Journal of Automatica Sinica, 8 (1), art. no. 9205687, pp. 239-248. Cited 145 times. https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER284-EPC doi: 10.1109/JAS.2020.1003393spa
dcterms.bibliographicCitationBreiding, M.J. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer (2009) Arch Intern Med, 63, pp. 2078-2086.spa
dcterms.bibliographicCitationCohen, J.P., Morrison, P., Dao, L. Covid-19 image data collection (2020) Arxiv, 2003, p. 11597. Cited 1115 times. arXivspa
dcterms.bibliographicCitationde La Iglesia Vayá, M. (2006) Bimcv Covid-19+: A Large Annotated Dataset of Rx and Ct Images from Covid-19 Patients 01174 (2020)spa
dcterms.bibliographicCitationDesai, S., Baghal, A., Wongsurawat, T., Jenjaroenpun, P., Powell, T., Al-Shukri, S., Gates, K., (...), Prior, F. Chest imaging representing a COVID-19 positive rural U.S. population (2020) Scientific Data, 7 (1), art. no. 414. Cited 21 times. www.nature.com/sdata/ doi: 10.1038/s41597-020-00741-6spa
dcterms.bibliographicCitationWinther, H.B. (2020) Covid-19 Image Repository. Cited 32 times. https://doi.org/10.25835/spa
dcterms.bibliographicCitationSignoroni, A., Savardi, M., Benini, S., Adami, N., Leonardi, R., Gibellini, P., Vaccher, F., (...), Farina, D. BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset (2021) Medical Image Analysis, 71, art. no. 102046. Cited 52 times. http://www.elsevier.com/inca/publications/store/6/2/0/9/8/3/index.htt doi: 10.1016/j.media.2021.102046spa
dcterms.bibliographicCitationHospitales, H.M. (2021) Covid Data save Lives. Cited 11 times. https://www.hmhospitales.com/coronavirus/covid-data-save-livesspa
dcterms.bibliographicCitationBustos, A., Pertusa, A., Salinas, J.-M., de la Iglesia-Vayá, M. PadChest: A large chest x-ray image dataset with multi-label annotated reports (2020) Medical Image Analysis, 66, art. no. 101797. Cited 171 times. http://www.elsevier.com/inca/publications/store/6/2/0/9/8/3/index.htt doi: 10.1016/j.media.2020.101797spa
dcterms.bibliographicCitation(2020) of the Valencia region BIMCV, M. I. D. Bimcv-covid19 – bimcv., /#1590859488150-148be708-c3f3 https://bimcv.cipf.es/bimcv-projects/bimcv-covid19spa
dcterms.bibliographicCitationIrvin, J. (2019) A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. Cited 141 times. aaai.v33i01.3301590 https://doi.org/10.1609/spa
dcterms.bibliographicCitationWang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., Summers, R.M. ChestX-ray8: Hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases (2017) Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-January, pp. 3462-3471. Cited 1710 times. ISBN: 978-153860457-1 doi: 10.1109/CVPR.2017.369spa
dcterms.bibliographicCitationKermany, D.S., Goldbaum, M., Cai, W., Valentim, C.C.S., Liang, H., Baxter, S.L., McKeown, A., (...), Zhang, K. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning (2018) Cell, 172 (5), pp. 1122-1131.e9. Cited 2239 times. https://www.sciencedirect.com/journal/cell doi: 10.1016/j.cell.2018.02.010spa
dcterms.bibliographicCitationJose Manuel, S. (2020) Medical Imaging Data Structure Extended to Multiple Modalities and Anatomical Regions. Arxiv Arxiv, 2010, p. 00434.spa
dcterms.bibliographicCitationStrickland, N.H. PACS (picture archiving and communication systems): Filmless radiology (Open Access) (2000) Archives of Disease in Childhood, 83 (1), pp. 82-86. Cited 58 times. doi: 10.1136/adc.83.1.82spa
dcterms.bibliographicCitationAlzate-Grisales, J.A. Cov-caldas: A new covid-19 chest x-ray dataset from state of caldas-colombia (2022) figshare https://doi.org/10.6084/m9.figshare.c.5833484.v1spa
dcterms.bibliographicCitation(2020) Colombia Confirma Su Primer Caso De COVID-19. Cited 9 times. https://www.minsalud.gov.co/Paginas/Colombia-confirma-su-primer-caso-de-COVID-19.aspxspa
dcterms.bibliographicCitationArias-Garzón, D. Covid-19 detection in x-ray images using convolutional neural networks (2021) Machine Learning with Applications, 6, p. 100138. Cited 35 times.spa
dcterms.bibliographicCitationRonneberger, O., Fischer, P., Brox, T. U-net: Convolutional networks for biomedical image segmentation (2015) Arxiv. Cited 411 times.spa
dcterms.bibliographicCitationHoward, A.G. Mobilenets: Efficient convolutional neural networks for mobile vision applications (2017) Arxiv Preprint, 1704, p. 04861. Cited 11263 times. arXivspa
dcterms.bibliographicCitationChollet, F. Xception: Deep learning with depthwise separable convolutions (Open Access) (2017) Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-January, pp. 1800-1807. Cited 7086 times. ISBN: 978-153860457-1 doi: 10.1109/CVPR.2017.195spa
dcterms.bibliographicCitationEfficientnet: Rethinking model scaling for convolutional neural networks (2019) In International Conference on Machine Learning, pp. 6105-6114. Cited 6187 times. PMLRspa
dcterms.bibliographicCitationSimonyan, K., Zisserman, A. Very deep convolutional networks for large-scale image recognition (2014) . Arxiv Preprint, 1409, p. 1556. Cited 41989 times. arXivspa
dcterms.bibliographicCitationSzegedy, C., Ioffe, S., Vanhoucke, V., Alemi, A.A. Inception-v4, inception-ResNet and the impact of residual connections on learning (Open Access) (2017) 31st AAAI Conference on Artificial Intelligence, AAAI 2017, pp. 4278-4284. Cited 6715 times. https://aaai.org/ocs/index.php/AAAI/AAAI17/indexspa
dcterms.bibliographicCitationHuang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q. Densely connected convolutional networks (Open Access) (2017) Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-January, pp. 2261-2269. Cited 19423 times. ISBN: 978-153860457-1 doi: 10.1109/CVPR.2017.243spa
dcterms.bibliographicCitationHe, K., Zhang, X., Ren, S., Sun, J. Identity mappings in deep residual networks (Open Access) (2016) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9908 LNCS, pp. 630-645. Cited 5056 times. https://www.springer.com/series/558 ISBN: 978-331946492-3 doi: 10.1007/978-3-319-46493-0_38spa
dcterms.bibliographicCitationHe, K., Zhang, X., Ren, S., Sun, J. Deep residual learning for image recognition (Open Access) (2016) Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016-December, art. no. 7780459, pp. 770-778. Cited 108313 times. ISBN: 978-146738850-4 doi: 10.1109/CVPR.2016.90spa
dcterms.bibliographicCitationRussakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., (...), Fei-Fei, L. ImageNet Large Scale Visual Recognition Challenge (Open Access) (2015) International Journal of Computer Vision, 115 (3), pp. 211-252. Cited 22545 times. http://www.kluweronline.com/issn/0920-5691/ doi: 10.1007/s11263-015-0816-yspa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
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dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/draftspa
dc.identifier.doi10.1038/s41597-022-01576-z
dc.subject.keywordsObject Detection;spa
dc.subject.keywordsDeep Learning;spa
dc.subject.keywordsIOUspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
dc.type.spahttp://purl.org/coar/resource_type/c_6501spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_6501spa


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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.