ASSESSMENT OF DIFFERENTIAL DIAGNOSIS OF BACTERIAL MENINGITIS FROM OTHER TYPES OF MENINGITIS USING FUZZY LOGIC AND NEURAL NETWORKS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

LANGARIZADEH MOSTAFA; KHAJEHPOUR ESMAT; SALARI RAHELEH; KHAJEHPOUR HASSAN

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Payavard Salamat Year:2017 | Volume:10 | Issue:5 Page(s): 453-460

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,035

Download:

Cites:

Information Journal Paper

Title

ASSESSMENT OF DIFFERENTIAL DIAGNOSIS OF BACTERIAL MENINGITIS FROM OTHER TYPES OF MENINGITIS USING FUZZY LOGIC AND NEURAL NETWORKS

Author(s)

LANGARIZADEH MOSTAFA | KHAJEHPOUR ESMAT | SALARI RAHELEH | KHAJEHPOUR HASSAN | Issue Writer Certificate

Keywords

FUZZY LOGICQ2

NEURAL NETWORKQ2

BACTERIAL MENINGITISQ2

Abstract

Background and Aim: BACTERIAL MENINGITIS detection is a complicated problem because of having several components in order to be diagnosed and distinguished from other types of meningitis. FUZZY LOGIC and NEURAL NETWORK, frequently used in expert systems, are able to distinguish such diseases. The purpose of this paper is to compare FUZZY LOGIC and artificial NEURAL NETWORKs for distinguishing BACTERIAL MENINGITIS from other types of meningitis.Materials and Methods: In this study to detect and distinguish BACTERIAL MENINGITIS from other types of meningitis, in the first step 6 attributes were selected by infectious disease specialists. In the second step, systems were designed by Matlab software. The systems were evaluated by 26 records of meningitis patients, and results were analyzed by SPSS software.Results: The evaluation showed that the accuracy, specificity and sensitivity of fuzzy method were 88%, 92% and 100% respectively and those of NEURAL NETWORK methods were 92%, 94% and 88% respectively. The Kappa test result in fuzzy and NEURAL NETWORK methods were 0.83 (p<0.001) and 0.83 (p<0.001). The areas under the ROC curves were 0.94 and 0.91 respectively.Conclusion: The sensitivity, the Kappa test results and the areas under the ROC curve of the FUZZY LOGIC method were better than NEURAL NETWORK method. However the FUZZY LOGIC method is more reliable to distinguish BACTERIAL MENINGITIS from other type of Meningitis, the evaluation result were obtained from 26 records of meningitis patient which were hospitalized in the same center leads to the study be still open.

Cites

No record.

References

No record.

Cite

APA: Copy

LANGARIZADEH, MOSTAFA, KHAJEHPOUR, ESMAT, SALARI, RAHELEH, & KHAJEHPOUR, HASSAN. (2017). ASSESSMENT OF DIFFERENTIAL DIAGNOSIS OF BACTERIAL MENINGITIS FROM OTHER TYPES OF MENINGITIS USING FUZZY LOGIC AND NEURAL NETWORKS. PAYAVARD-SALAMAT, 10(5), 453-460. SID. https://sid.ir/paper/149742/en

Vancouver: Copy

LANGARIZADEH MOSTAFA, KHAJEHPOUR ESMAT, SALARI RAHELEH, KHAJEHPOUR HASSAN. ASSESSMENT OF DIFFERENTIAL DIAGNOSIS OF BACTERIAL MENINGITIS FROM OTHER TYPES OF MENINGITIS USING FUZZY LOGIC AND NEURAL NETWORKS. PAYAVARD-SALAMAT[Internet]. 2017;10(5):453-460. Available from: https://sid.ir/paper/149742/en

IEEE: Copy

MOSTAFA LANGARIZADEH, ESMAT KHAJEHPOUR, RAHELEH SALARI, and HASSAN KHAJEHPOUR, “ASSESSMENT OF DIFFERENTIAL DIAGNOSIS OF BACTERIAL MENINGITIS FROM OTHER TYPES OF MENINGITIS USING FUZZY LOGIC AND NEURAL NETWORKS,” PAYAVARD-SALAMAT, vol. 10, no. 5, pp. 453–460, 2017, [Online]. Available: https://sid.ir/paper/149742/en

Related Journal Papers