Artificial neural network models to support the diagnosis of pleural tuberculosis in adult patients
Artificial neural network models to support the diagnosis of pleural tuberculosis in adult patients
Data
2013
Autores
Seixas, J. M.
Faria, J.
Filho, J. B. O. Souza
Vieira, A. F. M.
Kritski, A.
Trajman, A.
Journal Title
Journal ISSN
Volume Title
Publisher
INT J TUBERC LUNG DIS
Resumo
BACKGROUND: Clinicians in countries with high tu-
berculosis (TB) prevalence often treat pleural TB based
on clinical grounds, as the availability and sensitivity of
diagnostic tests are poor.
OBJECTIVE: To evaluate the role of artificial neural net-
works (ANN) as an aid for the non-invasive diagnosis of
pleural TB. These tools can be used in simple computer
devices (tablets) without remote internet connection.
METHODS: The clinical history and human immuno-
deficiency virus (HIV) status of 137 patients were pro-
spectively entered in a database. Both non-linear ANN
and the linear Fisher discriminant were used to calculate
performance indexes based on clinical grounds. The same
procedure was performed including pleural fluid test
results (smear, culture, adenosine deaminase, serology
and nucleic acid amplification test). The gold standard
was any positive test for TB.
RESULTS: In pre-test modelling, the neural model
reached >90% accuracy (Fisher discriminant 74.5%).
Under pre-test conditions, ANN had better accuracy
compared to each test considered separately.
CONCLUSIONS: ANN are highly reliable for diagnos-
ing pleural TB based on clinical grounds and HIV status
only, and are useful even in remote conditions lacking
access to sophisticated medical or computer infrastruc-
ture. In other better-equipped scenarios, these tools
should be evaluated as substitutes for thoracocentesis
and pleural biopsy.
Description
Palavras-chave
Pleurisy, accuracy, artificial intelligence, tuberculosis, diagnosis.
Citação
Seixas JM, Faria J, Souza Filho JB, Vieira AF, Kritski A, Trajman A. Artificial neural network models to support the diagnosis of pleural tuberculosis in adult patients. Int J Tuberc Lung Dis. 2013 May;17(5):682-6. doi: 10.5588/ijtld.12.0829.