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A machine learning solution for bed occupancy issue for smart healthcare sector
dc.contributor.author | Gochhait, Dr Saikat | spa |
dc.contributor.author | De-La-Hoz-Franco, Emiro | spa |
dc.contributor.author | Shaheen, Qaisar | spa |
dc.contributor.author | Diaz Martinez, Jorge Luis | spa |
dc.contributor.author | Piñeres Espitia, Gabriel Dario | spa |
dc.contributor.author | MERCADO POLO, DARWIN | spa |
dc.date.accessioned | 2022-08-25T00:01:36Z | |
dc.date.available | 2022 | |
dc.date.available | 2022-08-25T00:01:36Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Gochhait, S., Butt, S.A., De-La-Hoz-Franco, E. et al. A Machine Learning Solution for Bed Occupancy Issue for Smart Healthcare Sector. Aut. Control Comp. Sci. 55, 546–556 (2021). https://doi.org/10.3103/S0146411621060043 | spa |
dc.identifier.issn | 0146-4116 | spa |
dc.identifier.uri | https://hdl.handle.net/11323/9475 | spa |
dc.description.abstract | The health care domain is a culmination and emergence of many other economic sectors that give different services from patient treatment to healing, protective, rehabilitation, and palliative care. The GDP consumes to facilitate health in terms of smart device development, clinical examinations, outsourcing, and tele-medication facilities. The Asian countries and less developed countries with a high population rate are facing health care services related issues. One of these countries is India. India has two types of health care services systems: (i) public service system and (ii) private system. The public health system, i.e., the government, provides facilities to patients as primary health centers (PHCs) through limited secondary and tertiary health institutions like hospitals in rural areas while the private service is owned by local practitioners and institutions. Both of these service providers are facing bed occupancy issues for patients due to a highly populated country. To overcome this issue, we propose a machine learning solution for patient admission scheduling autonomously. The proposed framework helps hospitals to enhance the decision process for bed occupancy for patients concerning their departments and their diseases. We have deployed our framework in real time environment and find that it facilitates the overall performance of bed allocation in the prescribed hospitals. | eng |
dc.format.extent | 12 páginas | spa |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | |
dc.publisher | Pleiades Publishing | spa |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | spa |
dc.rights | © 2022 Springer Nature Switzerland AG. Part of Springer Nature. | spa |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | spa |
dc.title | A machine learning solution for bed occupancy issue for smart healthcare sector | eng |
dc.type | Artículo de revista | spa |
dc.identifier.url | https://doi.org/10.3103/S0146411621060043 | spa |
dc.source.url | https://link.springer.com/article/10.3103/S0146411621060043 | spa |
dc.rights.accessrights | info:eu-repo/semantics/embargoedAccess | spa |
dc.identifier.doi | 10.3103/S0146411621060043 | spa |
dc.identifier.eissn | 1558-108X | spa |
dc.identifier.instname | Corporación Universidad de la Costa | spa |
dc.identifier.reponame | REDICUC - Repositorio CUC | spa |
dc.identifier.repourl | https://repositorio.cuc.edu.co/ | spa |
dc.publisher.place | United States | spa |
dc.relation.ispartofjournal | Automatic Control and Computer Sciences | spa |
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dc.subject.proposal | Algorithms | eng |
dc.subject.proposal | Bed occupancy rate | eng |
dc.subject.proposal | Healthcare | eng |
dc.subject.proposal | Machine learning | eng |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | spa |
dc.type.content | Text | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.redcol | http://purl.org/redcol/resource_type/ART | spa |
dc.type.version | info:eu-repo/semantics/publishedVersion | spa |
dc.relation.citationendpage | 556 | spa |
dc.relation.citationstartpage | 546 | spa |
dc.relation.citationissue | 6 | spa |
dc.relation.citationvolume | 55 | spa |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
dc.rights.coar | http://purl.org/coar/access_right/c_f1cf | spa |
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