Big Data Analysis of Traditional Knowledge-based Ayurveda Medicine

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Modern medicine has embraced data-driven understanding of health, principally through electronic medical records. However, Ayurveda, which is the dominant traditional medicine system in India, much of it is still practiced without digital records.


In this study, 353,000 patients’ data were captured digitally by ~300 Ayurveda doctors over teleconsultation and in-person consultations. The entire dataset was analyzed based on age, sex, region, chronicity, Vikriti, disease morbidity, and comorbitidy and reported effectiveness of the treatment.


Younger patients were found to use more Ayurveda telemedicine, but all age groups were well represented. It was found that 82% patients had disease chronicity greater than 1 year. About 85% of the diseases were related to 6 organ systems, digestive (30.6%), endocrine (14.6%), skeleton (13.5%), skin (11.2%), nervous (7.6%), and respiratory (7.4%). The network analysis of the data revealed difference in sex and age-based patterns. Disease of endocrine and cardiovascular systems become comorbid for patient population at older age-groups as also observed in case of modern medicines.


Within the limitations of using practice data from a single large group of Ayurveda practitioners, this represents the first data-driven view of Ayurveda practice in India. In spite of 82% of all the patients having chronic diseases, Ayurveda treatment offered complete or partial relief in more than 76% of cases, and only 0.9% reported aggravation in symptoms.

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