Neuro-fuzzy based Anaemia diagnosis using LabVIEW

Anaemia is one of the most common blood diseases in today’s population, which has to be treated at its early stage. Anaemia is a condition where the haemoglobin level present in the blood drops below the normal level or decreases in the red blood cells count. Assisting professionals in the healthcare field with proper technologies plays a vital role in improving the quality of treatment. We propose a novel computational approach using LabVIEW fuzzy logic for the diagnosis of anaemia. Replacing an existing methodology with a prediction model eliminates human intervention so that errors caused by humans are avoided. It predicts not only the presence or absence of anaemia but also a type and severity of anaemia based on the Complete Blood Count test parameters. A 616 unit test has been implemented using Caraya unit test framework, ensuring the proper functioning of the proposed application. Anaemia predictor application provides an interactive GUI to the user and also provides us the facility to maintain a health database.