With the proliferation of big data, the need for intelligent and automated systems has risen. This need is probably felt the most in the field of health care, especially in the area of blood transfusion, since they require supplies at the earliest. Currently, transfusion services are heavily manual in nature, which is not ideal. The rising demand for blood and the decline in donation rates has put a lot of strain on the blood donation supply chain. Hence, creating intelligent systems that can make decisions and improve communication across the supply chain is of great importance. In this paper, we are going to give a general summary of the various machine learning techniques which have been applied to this domain and compare their advantages and disadvantages.
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