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Conceptual Model of Professional Supervision Study Based on Data Mining: A Study in the Regional Council of Nutritionists of the 4th Brazilian Region (Rio de Janeiro and Espirito Santo States)

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Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings

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Abstract

The amount of data accumulated over the inspections carried out by the Professional Councils is massive and dimensionality poses problems. Through the use of data mining, it is possible to expose behavior patterns of the companies and supervised professionals that, if known and disclosed, would have great potential for use in the management of inspections and subsidizing future decision-making. In this scenario, the objective of the present work is to generate useful information from the databases through data mining techniques, while exposing behavior patterns of the observed variables. A case study from the Regional Council of Nutritionists of the 4th Region of Brazil (states of Rio de Janeiro and Espirito Santo) helps to understand these objectives. The steps of Definition and Data Collection was performed; Data Selection, Pre-processing, Sanitization and Transformation, Data Mining and Analysis, and Discussion of Results. In the last step, the J48 classification method is used. The decision trees generated by the recommended method pointed out that it is possible to find a result trend and potential patterns in the proposed outcomes for the data mining process using the database from previous inspections.

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References

  1. B. Neves, A. Raimundo, Z. Obermeyer, The quiet revolution of big data in medicine. Med. Int. 24(4) (2017). https://doi.org/10.24950/rspmi/Perspective/2017

  2. V.V. Estrela, A.C.B. Monteiro, R.P. França, Y. Iano, A. Khelassi, N. Razmjooy, Health 4.0: applications, management, technologies and review. Med. Tech. J. 2(4), 262–276 (2019). https://doi.org/10.26415/2572-004X-vol2iss1p262-276.262

    Article  Google Scholar 

  3. V.V. Estrela, O. Saotome, H.J. Loschi, D.J. Hemanth, W.S. Farfan, R.J. Aroma, C. Saravanan, E.G.H. Grata, Emergency response cyber-physical framework for landslide avoidance with sustainable electronics. Technologies 6, 42 (2018). https://doi.org/10.3390/technologies6020042

    Article  Google Scholar 

  4. M.d.F. Pina, M.S. Carvalho, GeoMed 2017: Visao mais profunda a partir de big data e pequenas areas. Cad. Saude Publica. 33(10) (2017). https://doi.org/10.1590/0102-311x00172017

  5. C.E.V. Marinho, V.V. Estrela, H.J. Loschi, N. Razmjooy, A.E. Herrmann, Y. Thiagarajan, M.P. Vishnevski, A.C.B. Monteiro, R.P. França, Y. Iano, A model for medical staff idleness minimization, in Proceedings of the 4th Brazilian Technology Symposium (BTSym’18). BTSym 2018. Smart Innovation, Systems and Technologies, ed. by Y. Iano, R. Arthur, O. Saotome, V. Vieira Estrela, H. Loschi, vol. 140, (Springer, Cham, 2019)

    Google Scholar 

  6. L.M. Abreu, H.R.M. Hora, J.J.A. Rangel, M. Erthal Jr., N. Razmjooy, V.V. Estrela, T. Edoh, G.G. de Oliveira, Y. Iano, A multi-criteria modelling for ranking CO2 emitting G20 countries from the Kaya and their impacts on elderly health, in Proceedings of the 5th Brazilian Technology Symposium (BTSym’19). BTSym 2019. Smart Innovation, Systems and Technologies, ed. by Y. Iano et al., (Springer, Cham, 2020)

    Google Scholar 

  7. L.C. Lobo, Inteligencia Artificial e Medicina. Rev. Bras. Educ. Med. 41(2), 185–193 (2017). https://doi.org/10.1590/1981-52712015v41n2esp

    Article  Google Scholar 

  8. N. Razmjooy, V.V. Estrela, H.J. Loschi, Entropy-based breast cancer detection in digital mammograms using world cup optimization algorithm. Int. J. Swarm Intellig. Res. (IJSIR) 11(3), 1–18 (2020). https://doi.org/10.4018/IJSIR.2020070101

    Article  Google Scholar 

  9. V.V. Estrela, J.M.R.S. Tavares, L. Wang, S. Fuqian, J. Hemanth, SPECIAL ISSUE: Soft Computing Techniques for Image Analysis in the Medical Industry – Current Trends, Challenges and Solutions, Editorial, IEEE Access, IEEE (2018)

    Google Scholar 

  10. D.N. Bernstein, A. Keswani, D. Ring, Perioperative risk adjustment for total shoulder arthroplasty: are simple clinically driven models sufficient? Clin. Orthop. Relat. Res. (2017). https://doi.org/10.1007/s11999-0165147-y

  11. C. Gibbons, S. Richards, J.M. Valderas, J. Campbell, Supervised machine learning algorithms can classify open-text feedback of doctor performance with human level accuracy. J. Med. Internet Res. (2017). https://doi.org/10.2196/jmir.6533

  12. A. Hautemaniere, A. Florentin, P. Hartemann, P.R. Hunter, Identifying possible deaths associated with nosocomial infection in a hospital by data mining. Am. J. Infect. Control (2011). https://doi.org/10.1016/j.ajic.2010.04.216

  13. Federal Brazilian Law N 6.583. Cria os Conselhos Federal e Regionais de Nutricionistas, regula o seu funcionamento, e d’a outras providˆencias. Pub. L. No. LEI No 6.583 (1978)

    Google Scholar 

  14. Federal Resolution CFN N 380. Dispoe Sobre a Definicao das Areas de Atuacao do Nutricionista e Suas Atribuicoes, Estabelece Parametros Numericos de Referencia, Por Area de Atuacao, e da Outras Providencias. Conselho Federal de Nutricionistas. Pub. L. No. RESOLUCAO CFN No 380 (2005)

    Google Scholar 

  15. D.C.C. Barbosa, M.A. Machado, Mineracao de Dados usando o software WizRule em Base de Dados de Compras de TI. Revista Eletronica de Sistemas de Informacao 6(1) (2007). https://doi.org/10.21529/RESI.2007.0601001

  16. A. Berson, S. Smith, K. Thearling, Building Data Mining Applications for CRM (McGraw-Hill, New York, 2000)

    MATH  Google Scholar 

  17. E.L. da Silva, E.M. Menezes Metodologia da Pesquisa e Elaboracao de Dissertacao (4th ed. rev. atual., Vol. 138) (2005)

    Google Scholar 

  18. A.C. Gil, Metodos e tecnicas de pesquisa social (Atlas, Sao Paulo, 2008)

    Google Scholar 

  19. CRN4. Inspection (Fiscalizacao). Visitas de Fiscalizacao (2019). Available in: http://www2.crn4.org.br/pg/fiscalizacao/visitasdefiscalizacao¿. Acessado em 08 Dec 2019

  20. J. Han, M. Kamber, Data Mining: Concepts and Techniques, 3rd edn. (Elsevier, Burlington, 2011)

    MATH  Google Scholar 

  21. J.D.J. Costa, F.C. Bernardini, J. Viterbo Filho, A mineracao de dados e a qualidade de conhecimentos extraıdos dos boletins de ocorrencia das rodovias federais brasileiras. AtoZ: Novas praticas em informacao e conhecimento 3(2), 139 (2014)

    Article  Google Scholar 

  22. Resolution CFN N 465. Dispoe sobre as atribuicoes do Nutricionista, estabelece parametros numericos mınimos de referencia no ambito do Programa de Alimentacao Escolar (PAE) e da outras providencias. Conselho Federal de Nutricionistas. Pub. L. No. RESOLUCAO CFN No 465 (2010)

    Google Scholar 

  23. Resolution CFN N 600. Dispoe sobre a definicao das areas de atuacao do nutricionista e suas atribuicoes, indica parametros numericos mınimos de referencia, por area de atuacao, para a efetividade dos servicos prestados a sociedade e de outras providencias. Conselho Federal de Nutricionistas. Pub. L. No. RESOLUC¸AO CFN No 600 (2018)

    Google Scholar 

  24. E. Frank, M.A. Hall, I.H. Witten, The WEKA Workbench. Online Appendix for Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann, San Francisco, 2016)

    Google Scholar 

  25. X. Wu, V. Kumar, J. Ross Quinlan, J. Ghosh, Q. Yang, H. Motoda, D. Steinberg, Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1), 1–37 (2008). https://doi.org/10.1007/s10115-007-0114-2

    Article  Google Scholar 

  26. J. Gama, Arvores de Decisao (2002). Last seen in 01/02/2020. https://www.dcc.fc.up.pt/ines/aulas/MIM/arvoresdedecisao.pdf

  27. Brazilian Ministry of Education, Manual de apoio para as atividades tecnicas do Nutricionista no ambito do PNAE (Fundo Nacional de Desenvolvimento da Educacao, Brasılia, 2018)

    Google Scholar 

  28. F. Landi, R. Liperoti, D. Fusco, S. Mastropaolo, D. Quattrociocchi, A. Proia, A. Russo, R. Bernabei, G. Onder, Prevalence and risk factors of sarcopenia among nursing home older residents. J. Gerontol. Ser. A 67A(1), 48–55 (2012). https://doi.org/10.1093/gerona/glr035

    Article  Google Scholar 

  29. C. Patronillo, M.T. Verıssimo, Suplementos proteicos e Sarcopenia no idoso –Artigo de Revis˜ao (Faculdade de Medicina. Universidade de Coimbra, Coimbra, 2015)

    Google Scholar 

  30. D.N. Bernstein, A. Keswani, D. Ring, Perioperative risk adjustment for total shoulder arthroplasty: are simple clinically driven models sufficient? Clin. Orthopaed. Relat. Res. 475(12), 2867–2874 (2017). https://doi.org/10.1007/s11999-016-5147-y

    Article  Google Scholar 

  31. M. Layzell, Improving the management of postoperative pain. Nurs. Times 101(26), 34–36 (2005)

    Google Scholar 

  32. Z. Wang, B.S. Balasubramani, I.F. Cruz, in ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics (UrbanGIS). Predictive Analytics Using Text Classification for Restaurant Inspections. Article No.: 14, pp. 1–4. https://doi.org/10.1145/3152178.3152192 (2017)

  33. M.J.A. Berry, G. Linoff, Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, 2nd edn. (Wiley, Indianapolis, 2004)

    Google Scholar 

  34. S.M. Weiss, N. Indurkhya, Predictive Data Mining: A Practical Guide (Morgan Kaufmann Publishers, San Francisco, 1998)

    MATH  Google Scholar 

  35. N.D. Hansen, Web Data Mining for Public Health Purposes. ArXiv, abs/1905.00829 (2019)

    Google Scholar 

  36. A. Trajman, N. Assuncao, M. Venturi, D. Tobias, V. Tochi, V. Brant, A preceptoria na rede basica da Secretaria Municipal de Saude do Rio de Janeiro: Opiniao dos profissionais de saude. Rev. Bras. Educ. Med. Rio de Janeiro 33(1), 24–31 (2009)

    Article  Google Scholar 

  37. F.D. Silva, V.V. Estrela, L.J. Matos, Hyperspectral analysis of remotely sensed images, in Sustainable Water Management in the Tropics and Subtropics-and Case Studies in Brazil, ed. by C. Biblio, O. Hensel, J. F. Selbach, vol. 2, 1st edn., (University of Kassel, Kassel, 2011), pp. 398–423. ISBN: 9788563337214

    Google Scholar 

  38. C.D. Leite, J.G. Rodrigues, T.D. Sousa, H.R. da Hora, IT Services Management and ISO 20000: A Case Study in an IT Remote Support Company (2014)

    Google Scholar 

  39. G.T. Monteiro, H.R. Hora, Pesquisa em Saúde Pública: como desenvolver e validar instrumentos de coleta de dados (2014)

    Google Scholar 

  40. M.D. Mussa, S.C. Souza, E.F. Freire, R.G. Cordeiro, H.R. da Hora, Business intelligence in education: An application of Pentaho software. Revista Produção e Desenvolvimento 4, 29–41 (2018)

    Article  Google Scholar 

  41. L.R. Martins, L.D. Pereira, L.M. Almeida, H.R. da Hora, H.G. Costa, Study on the most appropriate scale for use in questionnaires: an experiment with Kano’s model. Vértices 13(1), 73–100 (2011)

    Article  Google Scholar 

  42. N. Rosso, P.J. Giabbanelli, Accurately inferring compliance to five major food guidelines through simplified surveys: applying data mining to the UK National Diet and nutrition survey. JMIR Pub. Health Surveill 4 (2018)

    Google Scholar 

  43. Y.E. Silva, C.G. Salgado, V.M. Conde, G.A. Conde, Data Mining Using Clustering Techniques as Leprosy Epidemiology Analyzing Model (DMBD, 2018)

    Google Scholar 

  44. R. Valter, S. Santiago, R. Ramos, M.V. Oliveira, L.O. Andrade, I.C. Barreto, in 2019 IEEE International Conference on E-Health Networking, Application & Services (HealthCom). Data Mining and Risk Analysis Supporting Decision in Brazilian Public Health Systems (2019), pp. 1–6

    Google Scholar 

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Authors and Affiliations

  1. Instituto Federal de Educação, Tecnologia e Ciência Fluminense (IFF), Campos dos Goytacazes, RJ, Brazil

    Anderson Luiz Ignacio de Lima, Rosane Justino de Sousa Lima & Henrique Rego Monteiro da Hora

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  1. Anderson Luiz Ignacio de Lima
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  2. Rosane Justino de Sousa Lima
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  3. Henrique Rego Monteiro da Hora
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Editors and Affiliations

  1. Abou Bakr Belkaïd University of Tlemcen, Tlemcen, Algeria

    Abdeldjalil Khelassi

  2. Telecommunications Department, Federal Fluminense University (UFF), Duque de Caxias, Rio de Janeiro, Brazil

    Vania Vieira Estrela

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de Lima, A.L.I., de Sousa Lima, R.J., da Hora, H.R.M. (2021). Conceptual Model of Professional Supervision Study Based on Data Mining: A Study in the Regional Council of Nutritionists of the 4th Brazilian Region (Rio de Janeiro and Espirito Santo States). In: Khelassi, A., Estrela, V.V. (eds) Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings. Springer, Cham. https://doi.org/10.1007/978-3-030-57552-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-57552-6_2

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