Tanzania is identified as one of the countries with a high TB burden in the world. One of the reasons for this situation is the ate identification of TB cases, hence delaying treatments and spreading the infection. The Global Fund Report (2018) identified 6 barriers for TB case detection in Tanzania which leads to poor treatment outcomes, higher tuberculosis prevalence, and possible multidrug-resistant TB increase. Among them are the low TB suspicion index and commitment in TB case detection among health care providers. Many TB patients are missed even after visiting health facilities. The reports found that over 100,000 cases are missed every year, suggesting a low TB suspicion index of the health care providers.
This project suggests a measure to address the low TB suspicion index of the health care providers by building a decision support system (DSS) using Artificial Intelligence (AI) techniques to provide assist healthcare providers during preliminary diagnosis to patients with the likelihood of having TB.
This project is lead by Mr Simon Mang’ombe Machera and Ms Aisha Mzee Mussa as principal investigators under the supervision of Dr Mathew Mndeme.