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Asociación Colombiana de Otorrinolaringología y Cirugía de Cabeza y cuello, Maxilofacial y Estética Facial (ACORL)

2022, Number 1

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Acta de Otorrinolaringología CCC 2022; 50 (1)

Risk of malignancy evaluation through data mining technic in patients with thyroid nodules with cytology study Bethesda IV

Baquero GRL, Diazgranados GE, León GE, Zambrano JF, Calixto GÁE, Rey AF, Palencia CA, Castañeda JF, León GE

Language: Spanish
References: 25
Page: 36-44
PDF size: 299.07 Kb.


ABSTRACT

Introduction: In the health field, each decision represents data, and data mining techniques have begun to be a promising methodology for the analysis of this information, especially in the design of predictive models. Methods: Analytical observational study; patients older than 15 years with a report of Bethesda IV after a fine needle aspiration biopsy that undergoing surgical management at the Hospital de San José in Bogotá. The data collected from those patients were included in three groups: sociodemographic-clinical information, cytology findings, and ultrasound reports. Analysis was performed using three technics: Naive Bayes, decision trees, and neural networks. Weka tool version 3.8.2 was used. Results: 195 patients out of 427, had a thyroid carcinoma pathology (45.6%). Better results were evidenced using cross-validation (10 fold) compared with a partition (66%), the Bayes technique had better results of correct classification (91.1%), than the tree technique (87.8%) and neural network (88.2%). Conclusions: The use of the Naive Bayes technique shows an important accuracy to determine the prediction of risk of malignancy in patients with a Bethesda IV cytological study, which would allow an adequate guide to the surgical management of patients.


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