| Autor: |
Priscyla Waleska, Simões, Geraldo Doneda da, Silva, Gustavo Pasquali, Moretti, Carla Sasso, Simon, Erik Paul, Winnikow, Silvia Modesto, Nassar, Lidia Rosi, Medeiros, Maria Inês, Rosa |
| Rok vydání: |
2013 |
| Předmět: |
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| Zdroj: |
Cadernos de saude publica. 31(1) |
| ISSN: |
1678-4464 |
| Popis: |
The aim of this study was to determine the accuracy of Bayesian networks in supporting breast cancer diagnoses. Systematic review and meta-analysis were carried out, including articles and papers published between January 1990 and March 2013. We included prospective and retrospective cross-sectional studies of the accuracy of diagnoses of breast lesions (target conditions) made using Bayesian networks (index test). Four primary studies that included 1,223 breast lesions were analyzed, 89.52% (444/496) of the breast cancer cases and 6.33% (46/727) of the benign lesions were positive based on the Bayesian network analysis. The area under the curve (AUC) for the summary receiver operating characteristic curve (SROC) was 0.97, with a Q* value of 0.92. Using Bayesian networks to diagnose malignant lesions increased the pretest probability of a true positive from 40.03% to 90.05% and decreased the probability of a false negative to 6.44%. Therefore, our results demonstrated that Bayesian networks provide an accurate and non-invasive method to support breast cancer diagnosis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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