Abstract

Dr. Ankit Pal* and Asst. Prof. (Dr) Laxmi 

ABSTRACT

Functional Abdominal Pain Disorders (FAPDs) account for nearly 80% of chronic abdominal pain cases in children and are diagnosed according to Rome IV criteria in the absence of identifiable organic pathology. In classical Ayurveda, this clinical spectrum may be understood in relation to Grahani Roga and Udara Shoola, conditions primarily associated with dysfunction of Agni and imbalance of the Doshas, thereby offering a holistic and constitution-based approach to diagnosis and management. This review explores the current and emerging role of Artificial Intelligence (AI) in the diagnosis of paediatric FAPDs and proposes an integrative framework that incorporates Ayurvedic diagnostic methods such as Prakriti assessment, Nadi Pariksha, Ashtavidha Pariksha, and Agni Bala evaluation as structured multimodal inputs for AI-driven clinical decision support systems. A narrative review of the literature was conducted using PubMed, Google Scholar, AYUSH Research Portal, and AYUSHdhara databases from 2000 to 2026, employing search terms including functional abdominal pain, FAPDs, children, AI, machine learning, Grahani Roga, Prakriti, Nadi Pariksha, Agni, Dosha, gut-brain axis, and Rome IV. The findings suggest that AI-based approaches, including machine learning classifiers such as SVM, ANN, and Random Forest, natural language processing-based symptom extraction, gut-microbiome modelling, and neuroimaging analysis, demonstrate diagnostic accuracy ranging from 53% to 87.5% in phenotyping paediatric abdominal pain. At the same time, AI-enabled digitisation of Ayurvedic diagnostic tools, particularly sensor-based Nadi Pariksha and machine learning-based Prakriti classification, has shown promising accuracy of up to 90% in Dosha identification. The conceptual overlap between Grahani Roga, often considered comparable to irritable bowel syndrome, and FAPDs offers a strong basis for integrative research. In conclusion, an AI-integrated Ayurvedic diagnostic model combining Prakriti profiling, digital Nadi Pariksha, Agni Bala indices, and modern biomarkers may provide a personalised, culturally relevant, and clinically useful approach to the diagnosis and management of FAPDs in children. However, large-scale paediatric validation studies are still needed to establish its clinical utility.