MATIBAI MODELING
Select a model, adjust key parameters, and let AI assist in diagnosing and designing therapy strategies for TB-HIV co-infection.
Selected Model:
Model ABC-EFGH123
a predictive model designed to analyze and assess the risk or progression of HIV-TB co-infection, supporting research and clinical decision-making through data-driven insights.
Selected Parameters:
Parameter 1:
- CD4 cell count
- Viral load
- Age Group
Parameter 2:
- TB diagnostic result (positive / negative)
- Chest X-ray findings (normal / abnormal)
- Previous TB treatment history
Parameter 1:
- Antiretroviral therapy (ART) status (on ART / not on ART)
- Duration of HIV infection
- Nutritional status (BMI category)
