Development and Assessment of an AI-Based Tuberculosis Diagnostic Tool in Tanzanian Hospitals: A Systematic Literature Review
Domaine:
healthcareType de record:
paper
Créateur:
MwaKibNdeSim
Éditeur:
Hôte:
The prevalence of tuberculosis (TB) in Tanzania is significant, necessitating effective diagnostic tools to improve patient outcomes. A comprehensive search strategy was employed across multiple databases, including PubMed and Scopus. Studies were screened based on predefined eligibility criteria. AI diagnostic tools showed moderate accuracy (mean AUC = 0.75 ± 0.10) in detecting TB cases. Existing AI-based TB diagnostics have shown promise but require further validation and refinement for widespread clinical use. Further research should focus on developing culturally sensitive models and integrating them into current healthcare systems.
Similaires
Integrating Indigenous Knowledge Systems into AI Development in Senegal: A Systematic Literature ReviewIntegrating Indigenous Knowledge Systems into AI Development in West Africa: A Systematic Literature ReviewPerceptions of AI-based learning tools among Tanzanian university students; systematic PRISMA reviewTalent Development Programme and Organizational Resilience: A Systematic Literature ReviewIntegration of Artificial Intelligence (AI) in Academic Libraries: A Systematic Literature ReviewAn investigation into the impact of digitalization in the SME’s development in Namibia: a systematic literature review