Abstract: India with nearly two lakh cases is estimated to possess the second highest number of patients with haemophilia, a lifelong bleeding disorder that forestalls blood from clotting. Hemophilia-A affects 1 in 5,000 male births within the U.S., and approximately 400 babies are born with hemophilia annually. Around 4 lakh people worldwide live with hemophilia. Hemophilia occurs in about 1 of each 5,000 male births. Supported recent study that used data collected on patients receiving care in federally funded hemophilia treatment centers during the amount 2012-2018, about 20,000 as many as 33,000 males within the us live with the disorder. It is very difficult to cure this kind of disease but can be handle with early diagnosis and proper treatment. The purpose of this paper is to establish some predictive models using Machine Learning algorithms by taking a real time Haemophilia dataset. In this paper, we have shown some real-time experiments and observations with the help of some Machine Learning algorithms, and also shown a clear picture on the predictive analysis on medical diagnosis of the Haemophilia using Machine Learning algorithms using which patients may get accurate data so as to diagnose better for their early treatment.

Keywords: Algorithm, Classifier, Haemophilia, Machine Learning, Prediction.

PDF | DOI: 10.17148/IJARCCE.2021.101210

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