Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   PAYAVARD-SALAMAT   FEBRUARY-MARCH 2020 , Volume 13 , Number 6 ; Page(s) 419 To 428.
 
Paper: 

Diagnosis of Pulmonary Tuberculosis Using Artificial Intelligence (Naive Bayes Algorithm)

 
 
Author(s):  Abbasi Hasanabadi Nastaran, FIROUZI JAHANTIGH FARZAD*, TABARSI PAYAM
 
* Department of Industrial Engineering, Faculty of Engineering Shahid Nikbakht, Sistan and Baluchestan University, Zahedan, Iran
 
Abstract: 
Background and Aim: Despite the implementation of effective preventive and therapeutic programs, no significant success has been achieved in the reduction of tuberculosis. One of the reasons is the delay in diagnosis. Therefore, the creation of a diagnostic aid system can help to diagnose early Tuberculosis. The purpose of this research was to evaluate the role of the Naive Bayes algorithm as a tool for the diagnosis of pulmonary Tuberculosis. Materials and Methods: In this practical study, the study population included Patients with TB symptoms, the study sample is recorded data of 582 individuals with primary Tuberculosis symptoms in Tehran's Masih Daneshvari Hospital. The data of samples were investigated in two classes of pulmonary Tuberculosis and non-Tuberculosis. A Naive Bayes algorithm for screening pulmonary Tuberculosis using primary symptoms of patients has been used in Python software version 3. 7. Results: Accuracy, sensitivity and specificity after the implementation of the Naive Bayes algorithm for diagnosis of pulmonary Tuberculosis were %95. 89, %93. 59 and %98. 53, respectively, and the Area under curve was calculated %98. 91. Conclusion: The performance of a Naive Bayes model for diagnosis of pulmonary Tuberculosis is accurate. This system can be used to help the patient and manage illness in remote areas with limited access to laboratory resources and healthcare professional and cause to diagnose early Tuberculosis. It can also lead to timely and appropriate proceedings to control the transmission of TB to other people and to accelerate the recovery of the disease.
 
Keyword(s): Pulmonary Tuberculosis,Naive Bayes Algorithm,Diagnosis,Artificial Intelligence
 
 
References: 
  • Not Registered.
  •  
  •  
 
Citations: 
  • Not Registered.
 
+ Click to Cite.
APA: Copy

Abbasi Hasanabadi, N., & FIROUZI JAHANTIGH, F., & TABARSI, P. (2020). Diagnosis of Pulmonary Tuberculosis Using Artificial Intelligence (Naive Bayes Algorithm). PAYAVARD-SALAMAT, 13(6 ), 419-428. https://www.sid.ir/en/journal/ViewPaper.aspx?id=781539



Vancouver: Copy

Abbasi Hasanabadi Nastaran, FIROUZI JAHANTIGH FARZAD, TABARSI PAYAM. Diagnosis of Pulmonary Tuberculosis Using Artificial Intelligence (Naive Bayes Algorithm). PAYAVARD-SALAMAT. 2020 [cited 2021August05];13(6 ):419-428. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=781539



IEEE: Copy

Abbasi Hasanabadi, N., FIROUZI JAHANTIGH, F., TABARSI, P., 2020. Diagnosis of Pulmonary Tuberculosis Using Artificial Intelligence (Naive Bayes Algorithm). PAYAVARD-SALAMAT, [online] 13(6 ), pp.419-428. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=781539.



 
 
Yearly Visit 43
 
 
Latest on Blog
Enter SID Blog