Knowledge Discovery in Databases: Comorbidities in Tuberculosis Cases

Author(s):Show less -

Carvalho, Isabelle ; Neiva, Mariane Barros ; Brandao Miyoshi, Newton Shydeo ; Crepaldi, Nathalia Yukie ; Bernardi, Filipe Andrade ; Lima, Vinicius Costa ; dos Santos, Ketlin Fabri ; de Andrade Mioto, Ana Clara ; Mozini, Mariana Tavares ; Galliez, Rafael Mello ; Sanchez, Mauro Niskier ; Kritski, Afranio Lineu ; Alves, Domingos ; Groen, D ; DeMulatier, C ; Paszynski, M ; Krzhizhanovskaya, VV ; Dongarra, JJ ; Sloot, PMA

• Document type: Journal article
• Source: COMPUTATIONAL SCIENCE - ICCS 2022, PT III; v. 13352, p. 11-pg., 2022-01-01.

Abstract

Unlike the primary condition under investigation, the term comorbidities define coexisting medical conditions that influence patient care during detection, therapy, and outcome. Tuberculosis continues to be one of the 10 leading causes of death globally. The aim of the study is to present the exploration of classic data mining techniques to find relationships between the outcome of TB cases (cure or death) and the comorbidities presented by the patient. The data are provided by TBWEB and represent TB cases in the territory of the state of Sao Paulo-Brazil, from 2006 to 2016. Techniques of feature selection and classification models were explored. As shown in the results, it was found high relevance for AIDS and alcoholism as comorbidities in the outcome of TB cases. Although the classifier performance did not present a significant statistical difference, there was a great reduction in the number of attributes and in the number of rules generated, showing, even more, the high relevance of the attributes: age group, AIDS, and other immunology in the classification of the outcome of TB cases. The explored techniques proved to be promising to support searching for unclear relationships in the TB context, providing, on average, a 73% accuracy in predicting the outcome of the cases according to characteristics that were analyzed. (AU)

• FAPESP's process: 22/00020-0 - DSS-TB: decision support system for Tuberculosis
• Grantee: Mariana Tavares Mozini
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• FAPESP's process: 20/01975-9 - Digital health for the End TB strategy: from linked data integration to a better evidence-based decision making
• Grantee: Domingos Alves
• Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants