A Predictive Approach for Blood Distribution through Data Mining Techniques

Abstract: Blood is extremely important thing for any hospital. But getting it on a right time is one of the difficult task for any hospital. Many times lack of blood results into delay in emergency operation. This problem can be solved by predicting the need of blood for any hospital in advance. This can be achieved by using data mining technique. Data mining will help to predict need of blood in any hospital for any duration of time. Predicted information will help to distribute blood which is mainly concentrated at few places in hospital across a country. This entire infrastructure will help us to keep right amount of blood at right place. Traditionally, blood record is usually managed by blood banks and hospitals in the form of hand written documents manually. These blood banks are located across different areas/cities in a country. Telephone is the only way of communication for these blood banks. So, in the case of any urgent requirement, blood has to carry from one blood bank to another and this process takes hours or days. Ultimately, this results into delay in operations or emergency can be produced. Solution to above problem is a proposing framework in which record is collected from sources and stored in a system then by prediction system will determine which hospital or blood banks need how much amount of blood. So, this system will definitely remove the problems come in traditional way, By using this system need of blood will definitely can be predicted in advance and it will help in emergencies.

Keywords: Data mining, Prediction analysis, K Means algorithm, Bulk Data Entry, Single Data Entry, REST web services.