Treatment of peptic ulcers with a Siddha medicine, “Sirucinni Uppu” and prediction with regression models

Abstract

Application of computational tools in medical science can assist physicians with analysis of disease. Herein, prediction based on a subset featured approach with the Siddha medical treatment dataset is utilized for peptic ulcers, using a simple linear regression (LR) based model as predictor, and measuring its effectiveness via error estimates and statistical significances. The herbal salt of Acalypha fruticosa (Siruccini Uppu) is dissolved in distilled water and administered to peptic ulcer patients in standard doses with honey before diet. The results were tabulated to show efficacy of treatment. Clinically ‘Sirucinni uppu’ is shown as an effective medicine in treating ‘Gunmam’ (peptic ulcer) patients with 80% satisfactory result, 10% fair, and 10% moderate result. The present analysis is beneficial in the effective usage of patterns and relationships reflected in datasets collected from real cases of peptic ulcer disease treatment. This approach of using such algorithms for early diagnosis of peptic ulcers could be employed by physicians to treat these patients more effectively. Keywords: Siddha, Peptic ulcer, Acalypha fruticosa, Sirucinni uppu, Gummam, Prediction, Linear regression, Gaussian processes, Error estimate