Fusion of Online Assessment Methods for Gynecological Examination Training: a Feasibility Study

• Autor(a) principal: SOARES,E.A.M.G.
• Data de Publicação: 2018
• Outros Autores: MORAES,R.M.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: TEMA (Sociedade Brasileira de Matemática Aplicada e Computacional. Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512018000300423
• topic: Fusion of assessment methods; online assessment; Fuzzy Naive Bayes; virtual reality; gynecological examination

ABSTRACT The objective of this paper was to determine if a fusion of online assessment methods is a feasible methodology for online assessment of performance of users inside virtual reality simulators. Three different forms of the Fuzzy Naive Bayes method based on statistical distributions were used to assess specific tasks and the fusion of information was performed by a Weighted Majority Voting system. Data was compiled representing a portion of the Gynecological Examination, which is a checkup examination that is routinely performed for women and is paramount in finding earlier cases of cervical cancer. Confusion matrices and Kappa coefficients were obtained using a Monte Carlo simulation for this method. From the analysis of these results, it is possible to confirm that this method performed well, with a substantial agreement degree.