The use of personalized medicine combined with artificial intelligence to monitor people with Covid-19
DOI:
https://doi.org/10.31686/ijier.vol10.iss4.3704Keywords:
artificial intelligence, personalized medicine, monitoringAbstract
Since the emergence of the pandemic caused by the SARS-CoV-2 virus (coronavirus disease or COVID-19), the generalities since its emergence, from the clinical picture, as well as the findings observed in AI (Artificial Intelligence) diagnostic methods applied to medicine personalized. This article is a literature review regarding the use of personalized medicine combined with artificial intelligence to monitor people with covid-19. The continuous evolution of intelligent systems aims to provide better reasoning and more efficient use of collected data. This use is not restricted to retrospective interpretation, that is, to provide diagnostic conclusions. It can also be extended to prospective interpretation, providing an early prognosis. That said, physicians who could be assisted by these systems find themselves in the gap between the clinical case and in-depth technical analyses. What is missing is a clear starting point for approaching the world of machine learning in medicine.
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Ali, M. et al. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet, v. 390, n. 22, p. 1211-1259, 2017.
Ayday, E; Fekri, F. An interative algorithm for trust management and adversary detection for delay tolerant networks. IEEE Trans. Mob. Comput, v. 11, n. 9, p. 1514–1531, 2012. DOI: https://doi.org/10.1109/TMC.2011.160
Backer, J. A. et al. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Euro Surveill, v. 25, n.5, 2020. DOI: https://doi.org/10.2807/1560-7917.ES.2020.25.5.2000062
Curtis, D. et al. Physiological signal monitoring in the waiting areas of an mergency room. In: Proceedings of body networks workshop, v. 2, p. 5 –8, 2008. DOI: https://doi.org/10.4108/ICST.BODYNETS2008.2968
Diaz Fernandez, U.; Rodriguez Ferreiro, A. O. Aplicaciones de la biotecnología en el desarrollo de la medicina personalizada. MEDISAN, v. 20, n. 5, p. 678-687, 2016.
Doughty, K. Smart Assistive Technology for People with Vision Impairment. i-Centre for Usable Home Technology Article of the Month, v. 3, n. 1, 2016.
Elmannai, W. Sensor-Based Assistive Devices for Visually-Impaired People: Current Status, Challenges, and Future Directions. Sensors, v. 17, n. 565, 2017. DOI: https://doi.org/10.3390/s17030565
Fan, Y. Network coding-based privacy preservation against traffic analysis in multi-hop wireless networks. Trans. Wirel. Commun. v.10, n.6, p.834–843, 2011. DOI: https://doi.org/10.1109/TWC.2011.122010.100087
Figueiredo, A. R. P. Uso terapêutico de tecnologias assistivas: direitos das pessoas com deficiência e visão. Belo Horizonte: Nescon, 2015.
Fonseca, C. A. et al. Authentication in the use of health sensors to remote patients with covid-19: a proposal for the telehealth center in the ebserh network. International Journal for Innovation Education and Research, v. 8, n. 8, 2020. DOI: https://doi.org/10.31686/ijier.vol8.iss8.2510
Guo, P.; Wang, J.I. A Lightweight Encryption Scheme Combined with Trust Management for Privacy-Preserving in Body Sensor Networks. J Med Syst. v.3 9, n. 190. 2015. DOI: https://doi.org/10.1007/s10916-015-0341-0
Hsu, C. L.; Lee, M. R; Su, C. H. The role of privacy protection in healthcare information systems adoption. J. Med. Syst, v. 31, n. 2. 2013. DOI: https://doi.org/10.1007/s10916-013-9966-z
Iriart, J. A. B. Medicina de precisão/medicina personalizada: análise crítica dos movimentos de transformação da biomedicina no início do século XXI. Cadernos de Saúde Pública, v. 35, n. 3, 2019. DOI: https://doi.org/10.1590/0102-311x00153118
Kumar, P; Lee, H. J. Security issues in health care applications using wireless medical sensor networks: a survey. Sensors. v. 11, n. 12, p. 55–91, 2013. DOI: https://doi.org/10.3390/s120100055
Leite, C. C. Inteligência artificial, radiologia, medicina de precisão e medicina personalizada. Radiologia Brasileira, v. 52, n. 6, p. 7-8, 2019. DOI: https://doi.org/10.1590/0100-3984.2019.52.6e2
Lizaraso-Caparo, F.; Ruiz-Mori, E. Medicina de precisión, un avance necesario. Horiz. Med, v. 18, n. 3, p. 4-5, 2018. DOI: https://doi.org/10.24265/horizmed.2018.v18n3.01
Ludermir, T. B. Inteligência Artificial e Aprendizado de Máquina: estado atual e tendências. Estudos Avançados, v. 35, n. 101, p. 85-94, 2021. DOI: https://doi.org/10.1590/s0103-4014.2021.35101.007
Marschollek, M. et al. Wearable sensors in healthcare and sensor-enhanced health information systems: all our tomorrows? Healthc Inform Res, v. 18, n. 2, p.97-104, 2012. DOI: https://doi.org/10.4258/hir.2012.18.2.97
Molero, G. D. et al. Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases. Sustainability, v. 13, n. 1137, 2021. DOI: https://doi.org/10.3390/su132011372
Nanshan, C. et al. Epidemiological and clinical characteristic of 9 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet. v. 395, 2020. DOI: https://doi.org/10.1016/S0140-6736(20)30211-7
Ramos, E. M. et al. COVID-19, rate of Case Factors and Nutritional Characteristics of Patients Dying in Italy and Brazil: A Critical Analysis. Global Journal of Health Science, v. 12, n. 133, 2020. DOI: https://doi.org/10.5539/gjhs.v12n7p133
Rodríguez, I. E. M. Inteligencia artificial como apoyo a intervenciones no farmacológicas para combatir la COVID-19. Rev. perú. med. exp. salud publica, v.37, n.3, p.582-584, 2019. DOI: https://doi.org/10.17843/rpmesp.2020.373.5704
Rodriguez Peron, J. M. Medicina de precisión y medicina basada en la evidencia. Rev Cub Med Mil, v. 48, n. 4, 2019.
Sighal, A.; Cowie, M. R. The role of wearables in heart failure. Curr Heart Fail Rep, v. 4, p. 125-132, 2020. DOI: https://doi.org/10.1007/s11897-020-00467-x
Silva, R. G. L.; Iriart, J. A. B. Como a comunidade internacional da medicina de precisão tem se posicionado diante dos desafios impostos pela pandemia da COVID-19? Cadernos de Saúde Pública, v. 37, n. 4, 2021. DOI: https://doi.org/10.1590/0102-311x00296920
Steinhubl, S. R; Muse, E. D.; Topol, E. J. The emerging field of mobile health. Sci Transl Med, v.l, n. 7, p. 283, 2015. DOI: https://doi.org/10.1126/scitranslmed.aaa3487
Vidal Ledo, M. et al. Medicina de precisión personalizada. Educ Med Super, v. 34, n. 1, 2020.
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Copyright (c) 2022 Adriana Simplicio Pereira Farias, Alessandro Carvalho da Fonseca, Danielle Bogo, Jéssica Carolina Garcia Avanci Moretti, José Amarildo Avanci Júnior, Marcelo Fontes da Silva, Regiane Santana da Conceição Ferreira Cabanha, Stephanie Pereira Farias, Josivaldo Godoy da Silva
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Accepted 2022-03-23
Published 2022-04-01
