A DEEP LEARNING FRAMEWORK FOR BLOOD GROUP PREDICTION

Abstract

The most crucial factor in blood transfusion is blood group categorisation and prediction. These days, they are carried out manually in a laboratory. This method requires physical labour since it takes a long time. Artificial intelligence is used to get beyond the limitations of traditional blood type prediction techniques. This includes the segmentation procedure used in image processing methods to identify blood group categorisation. To identify the components of blood, MATLAB simulations are used. The variety of blood is governed by the ABO and Rh group systems after blood samples are collected, processed, and pictures are identified using feature extraction. The created approach is used to address the shortcomings of the traditional procedure. This lowers a number of manual mistakes. Therefore, the artificial intelligence-based image processing method aids in the quick and error-free categorisation of blood.