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De Melo Ribeiro, Henrique, Arnold, Ahran, Howard, James P., Shun-Shin, Matthew J., Zhang, Ying, Francis, Darrel P., Lim, Phang B., Whinnett, Zachary and Zolgharni, Massoud ORCID: https://orcid.org/0000-0003-0904-2904 (2022) ECG-based real-time arrhythmia monitoring using quantized deep neural networks: a feasibility study. Computers in Biology and Medicine, 143. p. 105249. ISSN 0010-4825

Azarmehr, Neda, Ye, Xujiong, Howard, James P., Lane, Elisabeth S., Labs, Robert, Shun-Shin, Matthew J., Cole, Graham D., Bidaut, Luc, Francis, Darrel P. and Zolgharni, Massoud ORCID: https://orcid.org/0000-0003-0904-2904 (2021) Neural architecture search of echocardiography view classifiers. Journal of Medical Imaging, 8 (03). ISSN 2329-4302

Howard, James P., Stowell, Catherine C., Cole, Graham D., Ananthan, Kajaluxy, Demetrescu, Camelia D., Pearce, Keith, Rajani, Ronak, Sehmi, Jobanpreet, Vimalesvaran, Kavitha, Kanaganayagam, G. Sunthar, McPhail, Eleanor, Ghosh, Arjun K., Chambers, John B., Singh, Amar P., Zolgharni, Massoud ORCID: https://orcid.org/0000-0003-0904-2904, Rana, Bushra, Francis, Darrel P. and Shun-Shin, Matthew J. (2021) Automated left ventricular dimension assessment using artificial intelligence developed and validated by a UK-wide collaborative. Circulation: Cardiovascular Imaging, 14 (5). pp. 405-415. ISSN 1941-9651

Howard, James P., Tan, Jeremy, Shun-Shin, Matthew J., Mahdi, Dina, Nowbar, Alexandra N., Arnold, Ahran D., Ahmad, Yousif, McCartney, Peter, Zolgharni, Massoud ORCID: https://orcid.org/0000-0003-0904-2904, Linton, Nick W. F., Sutaria, Nilesh, Rana, Bushra, Mayet, Jamil, Rueckert, Daniel, Cole, Graham D. and Francis, Darrel P. (2019) Improving ultrasound video classification: an evaluation of novel deep learning methods in echocardiography. Journal of Medical Artificial Intelligence.

Cole, Graham D., Dhutia, Niti M., Shun-Shin, Matthew J., Willson, Keith, Harrison, James, Raphael, Claire E., Zolgharni, Massoud ORCID: https://orcid.org/0000-0003-0904-2904, Mayet, Jamil and Francis, Darrel P. (2015) Defining the real-world reproducibility of visual grading of left ventricular function and visual estimation of left ventricular ejection fraction: impact of image quality, experience and accreditation. The International Journal of Cardiovascular Imaging, 31 (7). pp. 1303-1314. ISSN 1569-5794