Artificial Intelligence in Shalya Tantra: Scope of AI in Diagnosis, Prognosis, and Ksharasutra Outcome

Abstract

Background: Shalya Tantra, an Ayurvedic surgical discipline, has extensive clinical data that remain largely unquantified. The healing of fistula in Ano has been reported to be 92-98% with Ksharasutra therapy, but the selection of the formulation of the thread and the intervals between its changes are subjective. This review evaluates the present and future possibilities of using AI in pattern recognition, prognosis, and prediction of outcomes in the diagnostic practice of Ksharasutra therapy.

Methods: A targeted narrative review of peer-reviewed literature from January 2015 to March 2026 was conducted using PubMed, Scopus, IEEE Xplore, and AYUSH Research Portal. The keywords included in the search were AI, machine learning, deep learning, Ayurveda, Shalya Tantra, Ksharasutra, and anorectal disorders. Studies that used AI in Ayurveda or anorectal surgery were included.

Results: AI is increasingly being applied in Ayurveda; however, its use is primarily confined to certain non-surgical areas. Previous machine learning-based models used to classify prakriti have shown high accuracy on small single-center datasets but have not yet been tested on external datasets. Although computer vision systems for wound assessment have been developed and sensor-based Nadi Pariksha exists, it has not yet been used in Shalya Tantra. No AI model has been validated for predicting Ksharasutra outcomes.

Conclusion: The possibilities of AI in Shalya Tantra are significant, but have not been fully explored. The aim of this study was to create standardized, annotated datasets for surgical conditions and develop AI-based predictive models for Ksharasutra. The integration should be a clinical application and knowledge-based approach.