Abstract
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.
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