Publication

Abstract :

Introduction: Hypothyroidism is an endocrinological disorder with a frequency of about 5% of the world's population, with causes ranging from autoimmune to geographic variability, gender, age, and iodine deficiency. The Billiewicker criteria for diagnosis were developed by the Indian Journal of Endocrine and Metabolic Society. There has never been a clear mentioning of hypothyroidism in Ayurvedic literature. However, a sizable portion of patients seek the same advice from Ayurvedic doctors. The results are greatly valued. The protocols pertaining to the diagnosis and treatment of hypothyroidism have not been previously explored or published as of this writing. AI can help us overcome this complexity by analysing complex data and identifying patterns. Aim And Objectives: To review Ayurvedic literature exploring the understanding and management of hypothyroidism, and synergizing Ayurveda with Artificial Intelligence. Materials And Methods: Discussion: Literature search was done from Ayurvedic Samhitas,pubmed,google scholar databases. By understanding hypothyroidism in Ayurveda, individuals can adopt a more natural and comprehensive approach to managing their condition, addressing the root causes and promoting overall well-being. By integrating the concepts of Santarpanotthajanya Vyadhi and Apatarpanotthajanya Vyadhi, their symptoms, and treatment protocol, the AI system validates diagnostic tools and enables personalized management protocols for hypothyroidism, thereby enhancing its clinical utility and value. From data collection to personalized treatment protocols, leveraging preprocessing, predictive analytics, and clinical validation for enhanced patient management. Conclusion: Thus, the integration of predictive analysis and diagnostics through AI techniques pave the way for a novel and innovative approach to manage hypothyroidism in Ayurveda.