Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Jose L Salmeron"'
Autor:
Samira Abbasgholizadeh Rahimi, France Légaré, Gauri Sharma, Patrick Archambault, Herve Tchala Vignon Zomahoun, Sam Chandavong, Nathalie Rheault, Sabrina T Wong, Lyse Langlois, Yves Couturier, Jose L Salmeron, Marie-Pierre Gagnon, Jean Légaré
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 9, p e29839 (2021)
BackgroundResearch on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease managem
Externí odkaz:
https://doaj.org/article/bf8b201178f8468395d586a4d280ebf1
Autor:
Jose L. Salmeron, Irina Arévalo
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-31 (2024)
Abstract Federated learning is an emerging machine learning approach that allows the construction of a model between several participants who hold their own private data. This method is secure and privacy-preserving, suitable for training a machine l
Externí odkaz:
https://doaj.org/article/95f4f1681ac84d4f80fb933b1403d2a3
Autor:
Samira Abbasgholizadeh Rahimi, Mojtaba Kolahdoozi, Arka Mitra, Jose L. Salmeron, Amir Mohammad Navali, Alireza Sadeghpour, Seyed Amir Mir Mohammadi
Publikováno v:
Mathematics, Vol 10, Iss 3, p 496 (2022)
Rheumatoid arthritis (RA) is a chronic inflammatory and long-term autoimmune disease that can lead to joint and bone erosion. This can lead to patients’ disability if not treated in a timely manner. Early detection of RA in settings such as primary
Externí odkaz:
https://doaj.org/article/c15c9e56ab8a48ea807ba5b0f198eb1e
Publikováno v:
Complexity, Vol 2019 (2019)
Externí odkaz:
https://doaj.org/article/4b135de403604efcaf85f09a3b99eb26
Autor:
Jose L. Salmeron
Publikováno v:
Series on Grey System ISBN: 9789811934230
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d8d94382d1d2f1da69bb93d7bb47bd9
https://doi.org/10.1007/978-981-19-3424-7_4
https://doi.org/10.1007/978-981-19-3424-7_4
Autor:
Jose L. Salmeron, Antonio Ruiz-Celma
Publikováno v:
Energies, Vol 12, Iss 1, p 90 (2018)
This research proposes an Elliot-based Extreme Learning Machine approach for industrial thermal processes regression. The main contribution of this paper is to propose an Extreme Learning Machine model with Elliot and Symmetric Elliot activation func
Externí odkaz:
https://doaj.org/article/197e7ff35ed94c3daf6096c800591390
Publikováno v:
Neurocomputing. 381:252-260
Understanding what Machine Learning models are doing is not always trivial. This is especially true for complex models such as Deep Neural Networks (DNN), which are the best-suited algorithms for modeling very complex and nonlinear relationships. But
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18ddb00d6e39f526055027f3aaf207df
https://doi.org/10.1016/j.neucom.2019.11.059
https://doi.org/10.1016/j.neucom.2019.11.059
Autor:
Jose L. Salmeron
Publikováno v:
Journal of Industrial Engineering and Management, Vol 2, Iss 2, Pp 319-322 (2009)
This special issue of the Journal of Industrial Engineering and Management is focused on new trends in Process Simulation and Modeling.
Externí odkaz:
https://doaj.org/article/3469d07ba4be4a48adf349749c279a83
Publikováno v:
Knowledge-Based Systems. 163:723-735
This paper present a comparison between Fuzzy Cognitive Map (FCM) learning approaches and algorithms. FCMs are fuzzy digraphs with weights and feedback loops, consisting of nodes interconnected through directed arcs mostly used for knowledge represen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddfd749b5a87c38c6df22a70fe6524c2
https://doi.org/10.1016/j.knosys.2018.09.034
https://doi.org/10.1016/j.knosys.2018.09.034
Publikováno v:
IEEE Transactions on Cybernetics. 49:211-220
This paper is focused on an innovative fuzzy cognitive maps extension called fuzzy grey cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems theory. These have become a useful framework for facing problems with high un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0df5194cc9fa28cfe107ca36edc90256
https://doi.org/10.1109/tcyb.2017.2771387
https://doi.org/10.1109/tcyb.2017.2771387