Use of Data Mining to Predict the Risk Factors Associated With Osteoporosis and Osteopenia in Women.
Osteoporosis has recently been acknowledged as a major public health issue in developed countries because of the decrease in the quality of life of the affected person and the increase in public costs due to complete or partial physical disability. The aim of this study was to use the J48 algorithm as a classification task for data from women exhibiting changes in bone densitometry. The study population included all patients treated at the diagnostic center for bone densitometry since 2010. Census sample data collection was conducted as all elements of the population were included in the sample. The service in question provides care to patients via the Brazilian Unified Health System and private plans. The results of the classification task were analyzed using the J48 algorithm, and among the dichotomized variables associated with a diagnosis of osteoporosis, the mean accuracy was 74.0 (95% confidence interval [CI], 61.0-68.0) and the mean area under the curve of the receiver operating characteristic (ROC) curve was 0.65 (95% CI, 0.64-0.66), with a mean sensitivity of 76.0 (95% CI, 76.0-76.0) and a mean specificity of 48.0 (95% CI, 46.0-49.0). The analyzed results showed higher values of sensitivity, accuracy, and curve of the ROC area in experiments conducted with individuals with osteoporosis. Most of the generated rules were consistent with the literature, and the few differences might serve as hypotheses for further studies.
Author Affiliations: Research Group in Information and Communications Technology in Health (Ms Lira, Ms Toniazzo de Abreu, Mr Mazzuchello, Dr Souza Pires, Mr Martins, and Dr Simões), Medicine Course (Ms Lira, Ms Toniazzo de Abreu, Ms Veiga Silva, Dr Rosa, and Dr Simões), and Graduate Program in Public Health (Dr Rosa, Dr Ceretta, and Dr Simões), Universidade do Extremo Sul Catarinense, Criciúma; and 4Vision Lab, Master of Science in Applied Computer, Universidade do Vale do Itajaí, São José, (Dr Comunello) and Graduate Program in Medical Sciences (Dr Souza Pires), Universidade Federal de Santa Catarina, Florianópolis, Brazil.
Carolina
C
Pedrassani de Lira
Larissa Letieli
LL
Toniazzo de Abreu
Ana Carolina
AC
Veiga Silva
Leandro Luiz
LL
Mazzuchello
Maria Inês
MI
Rosa
Eros
E
Comunello
Maria Marlene
MM
de Souza Pires
Luciane Bisognin
LB
Ceretta
Paulo João
PJ
Martins
Priscyla Waleska
PW
Simões
D000368:Aged; D000465:Algorithms; D001938:Brazil; D003430:Cross-Sectional Studies; D057225:Data Mining; D005260:Female; D006801:Humans; D008875:Middle Aged; D010024:Osteoporosis / Q000175:diagnosis* / Q000000981:diagnostic imaging; D011788:Quality of Life; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity