Convolutional & Recurrent Neural Networks for The Detection of Valvular Heart Diseases in Phonocardiogram Recordings
ADU Professor of Biomedical Engineering, Professor Luay Fraiwan and his former ADU undergraduate student from the electrical and computer engineering department, Engineer Mohanad Alkhodari, used cutting-edge deep learning techniques in Artificial Intelligence (AI) to propose a method to accurately classify five major types of valvular heart disease (VHD).
ADU Professor of Biomedical Engineering, Professor Luay Fraiwan and his former ADU undergraduate student from the electrical and computer engineering department, Engineer Mohanad Alkhodari, used cutting-edge deep learning techniques in Artificial Intelligence (AI) to propose a method to accurately classify five major types of valvular heart disease (VHD). Published in the top-ranked Journal of Computer Methods and Programs in Biomedicine, the scholars conclude that their method paves the way towards implementing deep learning models in VHD identification under clinical settings to assist clinicians in decision making and reduce errors in clinical diagnosis.
Associate Provost for Research and Academic Development, Professor Philip Hamill, said: “Congratulations to both scholars for publishing such an important research paper which has the potential to save lives. This is a remarkable achievement for Mohanad who won ADU’s undergraduate research competition and the UAE Ministry of Health and Prevention Innovations in Health Hackathon in 2017 to produce research of this quality at the early stage of his academic career. I wish him every success and have no doubt he will make further significant contributions to knowledge and innovation”.
Reference: Alkhodari, M. and Fraiwan, L, 2021. Convolutional and recurrent neural networks for the detection of valvular heart diseases in phonocardiogram recordings, Computer Methods and Programs in Biomedicine and Vol. 200: https://doi.org/10.1016/j.cmpb.2021.105940