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Cov-caldas: A new COVID-19 chest X-Ray dataset from state of Caldas-Colombia
dc.contributor.author | Alzate-Grisales, Jesús Alejandro | |
dc.contributor.author | Mora-Rubio, Alejandro | |
dc.contributor.author | Arteaga-Arteaga, Harold Brayan | |
dc.contributor.author | Bravo-Ortiz, Mario Alejandro | |
dc.contributor.author | Arias-Garzón, Daniel | |
dc.contributor.author | López-Murillo, Luis Humberto | |
dc.contributor.author | Mercado-Ruiz, Esteban | |
dc.contributor.author | Villa-Pulgarin, Juan Pablo | |
dc.contributor.author | Cardona-Morales, Oscar | |
dc.contributor.author | Orozco-Arias, Simon | |
dc.contributor.author | Buitrago-Carmona, Felipe | |
dc.contributor.author | Palancares-Sosa, Maria Jose | |
dc.contributor.author | Martínez-Rodríguez, Fernanda | |
dc.contributor.author | Contreras-Ortiz, Sonia H. | |
dc.contributor.author | Saborit-Torres, Jose Manuel | |
dc.contributor.author | Montell Serrano, Joaquim Ángel | |
dc.contributor.author | Ramirez-Sánchez, María Mónica | |
dc.contributor.author | Sierra-Gaber, ario Alfonso | |
dc.contributor.author | Jaramillo-Robled, Oscar | |
dc.contributor.author | de la Iglesia-Vayá, Maria | |
dc.contributor.author | Tabares-Soto, Reinel | |
dc.date.accessioned | 2023-07-21T16:24:12Z | |
dc.date.available | 2023-07-21T16:24:12Z | |
dc.date.issued | 2022 | |
dc.date.submitted | 2023 | |
dc.identifier.citation | Alzate-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.uri | https://hdl.handle.net/20.500.12585/12339 | |
dc.description.abstract | The 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.extent | 10 páginas | |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Scientific Data, 9(1) | spa |
dc.title | Cov-caldas: A new COVID-19 chest X-Ray dataset from state of Caldas-Colombia | spa |
dcterms.bibliographicCitation | Wang, 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.2020.1585 | spa |
dcterms.bibliographicCitation | Anis, 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.2020.3028390 | spa |
dcterms.bibliographicCitation | Ohata, 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.2020.1003393 | spa |
dcterms.bibliographicCitation | Breiding, 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.bibliographicCitation | Cohen, J.P., Morrison, P., Dao, L. Covid-19 image data collection (2020) Arxiv, 2003, p. 11597. Cited 1115 times. arXiv | spa |
dcterms.bibliographicCitation | de 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.bibliographicCitation | Desai, 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/s41597-020-00741-6 | spa |
dcterms.bibliographicCitation | Winther, H.B. (2020) Covid-19 Image Repository. Cited 32 times. https://doi.org/10.25835/ | spa |
dcterms.bibliographicCitation | Signoroni, 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.2021.102046 | spa |
dcterms.bibliographicCitation | Hospitales, H.M. (2021) Covid Data save Lives. Cited 11 times. https://www.hmhospitales.com/coronavirus/covid-data-save-lives | spa |
dcterms.bibliographicCitation | Bustos, 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.2020.101797 | spa |
dcterms.bibliographicCitation | (2020) of the Valencia region BIMCV, M. I. D. Bimcv-covid19 – bimcv., /#1590859488150-148be708-c3f3 https://bimcv.cipf.es/bimcv-projects/bimcv-covid19 | spa |
dcterms.bibliographicCitation | Irvin, 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.bibliographicCitation | Wang, 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.2017.369 | spa |
dcterms.bibliographicCitation | Kermany, 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.2018.02.010 | spa |
dcterms.bibliographicCitation | Jose Manuel, S. (2020) Medical Imaging Data Structure Extended to Multiple Modalities and Anatomical Regions. Arxiv Arxiv, 2010, p. 00434. | spa |
dcterms.bibliographicCitation | Strickland, 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.83.1.82 | spa |
dcterms.bibliographicCitation | Alzate-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.v1 | spa |
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.aspx | spa |
dcterms.bibliographicCitation | Arias-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.bibliographicCitation | Ronneberger, O., Fischer, P., Brox, T. U-net: Convolutional networks for biomedical image segmentation (2015) Arxiv. Cited 411 times. | spa |
dcterms.bibliographicCitation | Howard, A.G. Mobilenets: Efficient convolutional neural networks for mobile vision applications (2017) Arxiv Preprint, 1704, p. 04861. Cited 11263 times. arXiv | spa |
dcterms.bibliographicCitation | Chollet, 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.2017.195 | spa |
dcterms.bibliographicCitation | Efficientnet: Rethinking model scaling for convolutional neural networks (2019) In International Conference on Machine Learning, pp. 6105-6114. Cited 6187 times. PMLR | spa |
dcterms.bibliographicCitation | Simonyan, K., Zisserman, A. Very deep convolutional networks for large-scale image recognition (2014) . Arxiv Preprint, 1409, p. 1556. Cited 41989 times. arXiv | spa |
dcterms.bibliographicCitation | Szegedy, 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/index | spa |
dcterms.bibliographicCitation | Huang, 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.2017.243 | spa |
dcterms.bibliographicCitation | He, 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_38 | spa |
dcterms.bibliographicCitation | He, 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.2016.90 | spa |
dcterms.bibliographicCitation | Russakovsky, 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-y | spa |
datacite.rights | http://purl.org/coar/access_right/c_abf2 | spa |
oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.hasversion | info:eu-repo/semantics/draft | spa |
dc.identifier.doi | 10.1038/s41597-022-01576-z | |
dc.subject.keywords | Object Detection; | spa |
dc.subject.keywords | Deep Learning; | spa |
dc.subject.keywords | IOU | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.cc | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.identifier.instname | Universidad Tecnológica de Bolívar | spa |
dc.identifier.reponame | Repositorio Universidad Tecnológica de Bolívar | spa |
dc.publisher.place | Cartagena de Indias | spa |
dc.subject.armarc | LEMB | |
dc.type.spa | http://purl.org/coar/resource_type/c_6501 | spa |
oaire.resourcetype | http://purl.org/coar/resource_type/c_6501 | spa |
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