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Patients who undergo mechanical heart valve replacements or have conditionslike Atrial Fibrillation have to take Vitamin K Antagonists (VKA) drugs toprevent coagulation of blood. These drugs have narrow therapeutic range andneed to be very closely monitored due to life threatening side effects. Thedosage of VKA drug is determined and revised by a physician based onProthrombin Time - International Normalised Ratio (PT-INR) value obtainedthrough a blood test. Our work aimed at predicting the maintenance dosage ofwarfarin, the present most widely recommended anticoagulant drug, using thede-identified medical data collected from 109 patients from Kerala. A SupportVector Machine (SVM) Regression model was built to predict the maintenancedosage of warfarin, for patients who have been undergoing treatment from aphysician and have reached stable INR values between 2.0 and 4.0.

Development of a Machine Learning Model and Mobile Application to Aid in Predicting Dosage of Vitamin K Antagonists Among Indian Patients