Zobrazeno 1 - 10
of 131
pro vyhledávání: '"A. Hajjam El Hassani"'
Publikováno v:
Journal of Imaging, Vol 10, Iss 2, p 30 (2024)
Breast cancer is considered one of the most-common types of cancers among females in the world, with a high mortality rate. Medical imaging is still one of the most-reliable tools to detect breast cancer. Unfortunately, manual image detection takes m
Externí odkaz:
https://doaj.org/article/080838f80a7646f594beb5ed55c88105
Publikováno v:
IEEE Access, Vol 10, Pp 100786-100796 (2022)
Heart disease has become a non-ignorable threat to human health in recent years. Once without timely diagnosis and treatment, patients often suffer disability or even death. However, the diagnosis accuracy directly relies on different doctors’ expe
Externí odkaz:
https://doaj.org/article/c1d736f3edcf4124b03191c3774d62ce
Publikováno v:
In Informatics in Medicine Unlocked 2020 19
Autor:
Abrar-Ahmad Zulfiqar, Delwende Noaga Damien Massimbo, Mohamed Hajjam, Bernard Gény, Samy Talha, Jawad Hajjam, Sylvie Ervé, Amir Hajjam El Hassani, Emmanuel Andrès
Publikováno v:
Frontiers in Physiology, Vol 12 (2021)
Introduction: The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. This was the basis for the “GER-e-TEC COVID study,” an e
Externí odkaz:
https://doaj.org/article/730a884ac8b3435290dfbf4777ebf38f
Publikováno v:
In Swarm and Evolutionary Computation May 2019 46:171-183
Publikováno v:
In Swarm and Evolutionary Computation February 2019 44:712-727
Autor:
Andrés, E. *, Meyer, L., Zulfiqar, A.-A., Hajjam, M., Talha, S., Bahougne, T., Ervé, S., Hajjam, J., Doucet, J., Jeandidier, N., Hajjam, El Hassani, A.
Publikováno v:
In Médecine des maladies métaboliques February 2019 13(1):75-87
Publikováno v:
In Operations Research for Health Care March 2018 16:59-71
Publikováno v:
Informatics in Medicine Unlocked, Vol 19, Iss , Pp 100330- (2020)
The prediction of cardiac disease helps practitioners make more accurate decisions regarding patients' health. Therefore, the use of machine learning (ML) is a solution to reduce and understand the symptoms related to heart disease. The aim of this w
Externí odkaz:
https://doaj.org/article/79e54a2a745e49658d089301c4cc35fa
Publikováno v:
In IFAC PapersOnLine July 2017 50(1):14662-14667