World Quantum Day in Egypt - Sunday 14 APR/24 (Talk 2)
#WQD #WQD2024 #WQD24 #AleQCG # QEGYPT #QWORLD
By Doaa Ahmed Shoieb
Abstract
Machine learning models have recently become very effective tools for diagnosing different cardiovascular diseases (CVDs). Hybrid quantum methods can be employed to enhance the capacities of classical machine learning models. Here, we propose a hybrid quantum multiclass cardiac pathologies classification (HQMC-CPC) model based on the proposed modified hardware efficient ansatz (MHEA). The proposed model achieves promising results in training and testing with the Automatic Cardiac Diagnosis Challenge (ACDC 2017) dataset. Experimental results showed that the proposed HQMC-CPC model is able to diagnose different CVDs with an average minimum performance gap of 3.19%. The average maximum improvement in terms of accuracy in CVDs diagnosis is 7.77%. Moreover, the proposed HQMC-CPC speeds up the testing process by around 60% and 40% compared to the classical classifiers and well-established HEA respectively.