Artificial Intelligence in Diagnostic Innovations for Resource-Constrained Healthcare Settings in Malawi: A Scoping Review

The rapid advancement of artificial intelligence (AI) in healthcare diagnostics has significant implications for resource-constrained settings like Malawi. A systematic search was conducted using databases such as PubMed and Google Scholar, with a focus on studies published between and . Inclusion criteria were defined based on specific AI techniques applied to disease diagnosis. AI applications showed promising results in resource-limited settings, particularly in areas where traditional diagnostics are challenging due to limited equipment and trained personnel. The review highlights the potential of AI technologies to improve diagnostic accuracy and efficiency in Malawi's healthcare system, though challenges remain regarding technology integration and workforce training. Expanding access to AI diagnostic tools should be accompanied by comprehensive training programmes for healthcare workers and policies that support technology adoption. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.