Personalised Vaccination Prediction for Hepatitis B using Machine Learning

Abstract

Every newborn baby is mandatorily given three doses of Hepatitis B vaccination. The baby gets its first dose of vaccine at the time of birth. The second dose is given in between 1 to 2 months and the third dosage between 6 to 8 months. The very fact that Hepatitis B vaccination is given at birth specifies the necessity and importance of prevention of diseases caused by Hepatitis B. Infection by Hepatitis B can be the cause of several serious liver diseases. Also its complexity is further increased due to the fact that once vaccinated, the immune system doesn‟t hold the response to Hepatitis B surface antigens for a long course of time. One also has to consider that there are not many treatments for the diseases caused by the Hepatitis B viruses. For people who are tested to be prone to HBV attack are advised to have a booster vaccination to set right their immune system. Some people with less immunity or immune memory have to take up the entire vaccination cycle of three doses again instead of the booster dose. Predicting if a patient needs a booster dose or revaccination depends upon a lot of factors. This project, with the help of machine learning, aims to achieve perfect prediction of vaccination type the patient has to undergo and it also recommends the amount of dosage that is suitable and sufficient for the person. It aims to achieve personalized recommendation of booster vaccinations for millions of people around the world.