A Predictive Analytics Framework for Blood Donor Classification

Kavita Pabreja, Akanksha Bhasin

OAI: oai:igi-global.com:277644 • DOI: 10.4018/IJBDAH.20210701.oa1

India faces numerous challenges to the meet ever-increasing demand of human blood so as to improve the health indicators across its rural and urban population. The gap between demand and supply can be fulfilled by increasing voluntary blood donations. Hence, it becomes important to understand the attitude of population towards blood donations. In this paper an effort has been made to identify features in order of their importance that affect the decision of a person to become a blood donor. This research uses extensive visualization techniques to get an insight into potential blood donor characteristics and then applies classification technique to classify youth of an Indian state university as donor or non-donor. The k-nearest neighbour classification algorithm discovers the relationship between attributes of blood donors and hence predicts the outcome. The important factors that dissuade potential donors from donating blood have been extracted that can be worked upon to meet the demand of blood to save human lives.

Data Analysis & Statistics Medical, Healthcare, and Life Sciences Health Information Systems