Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Mercedes Cabrerizo"'
Autor:
Ahmed Hossam Mohammed, Ulyana Morar, Mercedes Cabrerizo, Hoda Rajaei, Alberto Pinzon, Ilker Yaylali, Malek Adjouadi
Publikováno v:
IEEE Access, Vol 10, Pp 1276-1288 (2022)
Background: Understanding functional connectivity (FC) patterns of epileptic brain networks as they relate to the presence or absence of interictal epileptiform discharges (IEDs) can enhance machine learning (ML) algorithms identifying them. Methods:
Externí odkaz:
https://doaj.org/article/0bc1af66db1a45269e10b61fb8ae6abf
A transfer learning approach based on gradient boosting machine for diagnosis of Alzheimer’s disease
Autor:
Mehdi Shojaie, Mercedes Cabrerizo, Steven T. DeKosky, David E. Vaillancourt, David Loewenstein, Ranjan Duara, Malek Adjouadi
Publikováno v:
Frontiers in Aging Neuroscience, Vol 14 (2022)
Early detection of Alzheimer’s disease (AD) during the Mild Cognitive Impairment (MCI) stage could enable effective intervention to slow down disease progression. Computer-aided diagnosis of AD relies on a sufficient amount of biomarker data. When
Externí odkaz:
https://doaj.org/article/c9fa70936ab14e7b870d1777f626fb10
Autor:
Ahmed Hossam Mohammed, Mercedes Cabrerizo, Ulyana Morar, Hoda Rajaei, Alberto Pinzon, Ilker Yaylali, Sergio Gonzales-Arias, Malek Adjouadi
Publikováno v:
IEEE Access, Vol 9, Pp 204-217 (2021)
Objective: This study demonstrates how functional connectivity (FC) patterns are affected in direct relation to the lobe that is mostly affected by seizures. Methods: The novel idea of penalized FC (pFC) maps is compared against standard FC maps in t
Externí odkaz:
https://doaj.org/article/ecef2d5440544e82b4fef7c5d1d5ec82
Autor:
Solale Tabarestani, Mohammad Eslami, Mercedes Cabrerizo, Rosie E. Curiel, Armando Barreto, Naphtali Rishe, David Vaillancourt, Steven T. DeKosky, David A. Loewenstein, Ranjan Duara, Malek Adjouadi
Publikováno v:
Frontiers in Aging Neuroscience, Vol 14 (2022)
With the advances in machine learning for the diagnosis of Alzheimer’s disease (AD), most studies have focused on either identifying the subject’s status through classification algorithms or on predicting their cognitive scores through regression
Externí odkaz:
https://doaj.org/article/536f73f3fc3e4a628ee05ef0cfe71225
Publikováno v:
IET Image Processing, Vol 14, Iss 15, Pp 3791-3801 (2020)
This study utilises a deep convolutional neural network (CNN) implementing regularisation and batch normalisation for the removal of mixed, random, impulse, and Gaussian noise of various levels from digital images. This deep CNN achieves minimal loss
Externí odkaz:
https://doaj.org/article/57b7f6c432c1439299551cc9c76aadfa
Autor:
Rosie E. Curiel Cid, David A. Loewenstein, Monica Rosselli, Jordi A. Matias‐Guiu, Daema Piña, Malek Adjouadi, Mercedes Cabrerizo, Russell M. Bauer, Aldrich Chan, Steven T. DeKosky, Todd Golde, Maria T. Greig‐Custo, Gabriel Lizarraga, Ailyn Peñate, Ranjan Duara
Publikováno v:
Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, Vol 11, Iss 1, Pp 550-559 (2019)
Abstract Introduction Culturally fair cognitive assessments sensitive to detecting changes associated with prodromal Alzheimer's disease are needed. Methods Performance of Hispanic and non‐Hispanic older adults on the Loewenstein‐Acevedo Scale of
Externí odkaz:
https://doaj.org/article/a1d7f35ab4fd485796f0d5e4d59c74d5
Autor:
Solale Tabarestani, Maryamossadat Aghili, Mohammad Eslami, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Rosie E. Curiel, David Loewenstein, Ranjan Duara, Malek Adjouadi
Publikováno v:
NeuroImage, Vol 206, Iss , Pp 116317- (2020)
Predicting the progression of Alzheimer’s Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning al
Externí odkaz:
https://doaj.org/article/f13e176f63a542e185a6eedf89aadf77
Autor:
Mehdi Shojaie, David A. Loewenstein, David E. Vaillancourt, Ranjan Duara, Malek Adjouadi, Steven T. DeKosky, Solale Tabarestani, Mercedes Cabrerizo
Publikováno v:
Journal of Alzheimer's Disease. 84:1497-1514
Background: Machine learning is a promising tool for biomarker-based diagnosis of Alzheimer’s disease (AD). Performing multimodal feature selection and studying the interaction between biological and clinical AD can help to improve the performance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17bc37c78c4c36d7297930aefefa9374
https://doi.org/10.3233/jad-210064
https://doi.org/10.3233/jad-210064
Autor:
Ilker Yaylali, Ahmed Hossam Mohammed, Sergio Gonzales-Arias, Alberto Pinzon, Hoda Rajaei, Malek Adjouadi, Ulyana Morar, Mercedes Cabrerizo
Publikováno v:
IEEE Access, Vol 9, Pp 204-217 (2021)
Objective : This study demonstrates how functional connectivity (FC) patterns are affected in direct relation to the lobe that is mostly affected by seizures. Methods : The novel idea of penalized FC (pFC) maps is compared against standard FC maps in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bd935be394fa19f1296bc126b681de8
https://ieeexplore.ieee.org/document/9305291/
https://ieeexplore.ieee.org/document/9305291/
Publikováno v:
IET Image Processing. 14:3791-3801
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8073c472472289defbf9ff67c775ee28
https://doi.org/10.1049/iet-ipr.2019.0931
https://doi.org/10.1049/iet-ipr.2019.0931