| Issue |
E3S Web of Conf.
Volume 388, 2023
The 4th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2022)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 6 | |
| Section | Big Data, Green Computing, and Information System | |
| DOI | https://doi.org/10.1051/e3sconf/202338802004 | |
| Published online | 17 May 2023 | |
Design of Computer-Aided-Diagnosis (CAD) for Self- Assessment Tuberculosis in Indonesia
1 Bioinformatics and Data Science Research Center, 11480 Bina Nusantara University, Indonesia
2 Computer Science Department BINUS Graduate Program, Master of Computer Science, 11480 Bina Nusantara University, Indonesia
* Corresponding author: faisal.asadi@binus.edu
Tuberculosis (TB) is one of the highest causes of death in Indonesia. The main reason is lack of the health facilities. Computer-aided diagnosis (CAD) is a tool for early treatment and screening of many diseases, including TB. This paper proposed a design of a CAD system in Indonesia specifically for TB. The design gives the analysis of self-assessment concepts, use-case diagrams, and black-box diagrams. The black box utilizes chest x-ray (CXR) data for the medical image processing (MIP) method, and artificial intelligence (AI) for classification and visualization of the TB. This CAD design of self-assessment of TB has a capability to help the health practitioners read and interpret the diagnosis result more easily.
© The Authors, published by EDP Sciences, 2023
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