This study investigates the integration of Artificial Intelligence (AI) techniques in analyzing user feedback on mobile health (mHealth) applications. By conducting a systematic literature review of 23 selected studies, it explores the effectiveness of sentiment analysis, machine learning models, and UX evaluation in improving mHealth usability and reliability. The findings indicate that larger datasets and balanced feature sets significantly enhance model performance. Moreover, the study highlights the need for culturally aware AI design, standard evaluation metrics, and hybrid models to improve digital health outcomes. Visual and comparative analyses support the proposed research directions and frameworks.