Unveiling the Efficacy of Unani Medicine in Female Disorders Through Machine Learning: Current Challenges and Opportunities

In the past decade, the healthcare sector has seen a noteworthy increase in the application of artificial intelligence (AI) technologies across various therapeutic domains. AI-powered technologies have been increasingly used in the context of female diseases within Unani medicine. This study unveils the efficacy of Unani medicine in female diseases through machine learning. This review abides by the preferred reporting items for systematic reviews and meta-analysis extensions for scoping reviews. Studies published after January 1, 2000, were included in 2000 to 2023. A total of 402 full-length articles were searched from the PubMed and Science direct. Two studies from published articles and two from the proposed dataset exclusively focused on the efficacy of Unani medicine, along with one cross-sectional study. This review demonstrates that this research has been conducted using various machine-learning techniques to detect the efficacy of Unani treatment in female disoder. Machine learning was also applied in a cross-sectional study on abnormal vaginal discharge and Mizaj. Machine learning models were used. While research on machine learning models in Unani herbal medicine is in its preliminary stages, the findings from the selected research suggest that ML methods can enhance the services provided by Unani practitioners to their patients. Nevertheless, future advancements should involve the application of diverse ML models across a broad spectrum of Unani treatments.