Comparative Clinical Evaluation of Artificial-Intelligence & Neural Language-Models Assisted Prescription versus Conventional Repertory based Prescription in Homoeopathy Assessing Improvement in Patient Reported Outcomes: Single-Blind, Randomized, Exploratory, Pilot Study

The findings of this pilot study could provide preliminary insights into the modernization of homoeopathic practice, education, and research. If AI-NLMs assisted prescribing demonstrates trends toward greater efficiency and effectiveness, it may suggest potential for reducing repertorization time, minimizing variability between prescribers, and enhancing patient outcomes. For students and early practitioners, AI-NLMs could serve as an exploratory educational aid, supporting their understanding of repertory and materia medica. Technologically, this trial would offer the first pilot-level systematic evidence on AI integration in homoeopathy, thereby laying the groundwork for larger, more definitive studies. At a broader level, the results may inform future discussions on the possible institutional and policy adoption of AI systems in homoeopathic hospitals, colleges, and research institutes, ultimately contributing to accessibility, credibility, and modernization of practice.