Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Luis Eduardo Juarez‐Orozco"'
Autor:
M. Yldau van der Ende, Luis Eduardo Juarez‐Orozco, Ingmar Waardenburg, Erik Lipsic, Remco A. J. Schurer, Hindrik W. van der Werf, Emelia J. Benjamin, Dirk Jan van Veldhuisen, Harold Snieder, Pim van der Harst
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 9, Iss 13 (2020)
Background Myocardial infarction is an important cause of morbidity and mortality in both men and women. Atypical or the absence of symptoms, more prevalent among women, may contribute to unrecognized myocardial infarctions and missed opportunities f
Externí odkaz:
https://doaj.org/article/dea8f7e29cb642c98ac480c0a1829d64
Autor:
Luis Eduardo Juarez-Orozco, Octavio Martinez-Manzanera, Sergey V. Nesterov, Sami Kajander, Juhani Knuuti
Publikováno v:
European Journal of Hybrid Imaging, Vol 2, Iss 1, Pp 1-15 (2018)
Abstract Background Machine learning (ML) represents a family of algorithms that has rapidly developed within the last years in a wide variety of knowledge areas. ML is able to elucidate and grasp complex patterns from data in order to approach predi
Externí odkaz:
https://doaj.org/article/b81252e330144254b13e09c1b30b2d71
Autor:
Ming Wai Yeung, Jan Walter Benjamins, Remco J. J. Knol, Friso M. van der Zant, Folkert W. Asselbergs, Pim van der Harst, Luis Eduardo Juarez-Orozco
Publikováno v:
Journal of Nuclear Cardiology, 29. SPRINGER
Journal of nuclear cardiology, 29(6), 3300-3310. Springer New York
Journal of nuclear cardiology, 29(6), 3300-3310. Springer New York
Background Advanced cardiac imaging with positron emission tomography (PET) is a powerful tool for the evaluation of known or suspected cardiovascular disease. Deep learning (DL) offers the possibility to abstract highly complex patterns to optimize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::037f5ced2507e67713ceb48e2db14cc5
https://doi.org/10.1007/s12350-022-02920-x
https://doi.org/10.1007/s12350-022-02920-x
Autor:
Prince Dadson, Luis Eduardo Juarez-Orozco, Eleni Rebelos, Anne Beate Langeland Marthinsen, Dariusz Moczulski, Kwame Anokye Amoabeng, Sanna Laurila
Publikováno v:
Clinical and Translational Imaging. 10:59-69
Purpose Positron emission tomography (PET) is a nuclear imaging technique that uses radiotracers to visualize metabolic processes of interest across different organs, to diagnose and manage diseases, and monitor therapeutic response. This systematic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d0a8dead21c536dc2a80fb69a138fff
https://doi.org/10.1007/s40336-021-00469-2
https://doi.org/10.1007/s40336-021-00469-2
Autor:
Riku Klén, Ming Wai Yeung, Juhani Knuuti, Luis Eduardo Juarez-Orozco, Jan Walter Benjamins, Antti Saraste, Teemu Maaniitty, Pim van der Harst
Publikováno v:
International Journal of Cardiology, 335, 130-136. ELSEVIER IRELAND LTD
Background: Standard computed tomography angiography (CTA) outputs a myriad of interrelated variables in the evaluation of suspected coronary artery disease (CAD). But an important proportion of obstructive lesions does not cause significant myocardi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cb7f8eee76be8788d40d2104a424ef7
https://hdl.handle.net/11370/83eb8597-5dd0-4442-9628-60b12fdfa355
https://hdl.handle.net/11370/83eb8597-5dd0-4442-9628-60b12fdfa355
Autor:
Maria Alexandra Arias-Mendoza, Sharon Selmen-Chattaj, Beatriz E. Dominguez-Mendez, Carlos Martínez-Sánchez, Karla Balderas-Muñoz, Carlos R. Sierra-Fernández, Luis Eduardo Juarez-Orozco, Jorge Padilla-Ibarra, Pim van der Harst, Oscar Calvillo-Argüelles, Hugo Rodríguez-Zanella
Publikováno v:
Chest. 158:1669-1679
Background OSA conveys worse clinical outcomes in patients with coronary artery disease. The STOP-BANG score is a simple tool that evaluates the risk of OSA and can be added to the large number of clinical variables and scores that are obtained durin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2d017286a455a6b2e2804af267f398a
https://doi.org/10.1016/j.chest.2020.03.074
https://doi.org/10.1016/j.chest.2020.03.074
Autor:
Juhani Knuuti, O. Martinez-Manzanera, Luis Eduardo Juarez-Orozco, Remco J.J. Knol, Carlos A. Sánchez-Catasús, Friso M. van der Zant
Publikováno v:
Journal of Nuclear Cardiology, 27(1), 147-155. SPRINGER
Background A significant number of variables are obtained when characterizing patients suspected with myocardial ischemia or at risk of MACE. Guidelines typically use a handful of them to support further workup or therapeutic decisions. However, it i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0a529d386883b391731875277455154
https://hdl.handle.net/11370/7cc7a2d7-cd80-4593-8cad-0bff8afe62fe
https://hdl.handle.net/11370/7cc7a2d7-cd80-4593-8cad-0bff8afe62fe
Autor:
Bipul R. Acharya, Dritan Agalliu, V.A. Alexandrescu, Zakaria Almuwaqqat, Rheure Alves-Lopes, Ken Arai, Wadih Arap, Victoria L. Bautch, Lisa M. Becker, Michelle P. Bendeck, Jan Walter Benjamins, Saptarshi Biswas, E. Boesmans, Livia L. Camargo, Peter Carmeliet, Munir Chaudhuri, Nicholas W. Chavkin, Ondine Cleaver, Clément Cochain, Michael S. Conte, Azzurra Cottarelli, Christie L. Crandall, Anne Cuypers, Andreas Daiber, Alan Dardik, Jui M. Dave, J.O. Defraigne, Wenjun Deng, Robert J. DeStefano, Devinder Dhindsa, Danny J. Eapen, Anne Eichmann, Christian El Amm, Omotayo Eluwole, Christian Faaborg-Andersen, Steven A. Fisher, Zorina S. Galis, Guillermo García-Cardeña, Xin Geng, Michael A. Gimbrone, Luis Gonzalez, Daniel M. Greif, Xiaowu Gu, Shuzhen Guo, Tara L. Haas, Omar Hahad, Pim van der Harst, Peter K. Henke, Karen K. Hirschi, C. Holemans, Gonçalo Hora de Carvalho, Song Hu, Jay D. Humphrey, Shabatun J. Islam, Xinguo Jiang, Luis Eduardo Juarez-Orozco, Angelos D. Karagiannis, Anita Kaw, Kaveeta Kaw, Fatemeh Kazemzadeh, A. Kerzmann, Alexander S. Kim, Ageliki Laina, Eva K. Lee, Jinyu Li, Wenlu Li, Chien-Jung Lin, Xiaolei Liu, Eng H. Lo, Josephine Lok, Mark W. Majesky, Ziad Mallat, Muzi J. Maseko, Dianna M. Milewicz, Amanda L. Mohabeer, Augusto C. Montezano, Giorgio Mottola, Thomas Münzel, Daniel D. Myers, Karla B. Neves, Mark R. Nicolls, MingMing Ning, Andrea T. Obi, Guillermo Oliver, Renata Pasqualini, Alessandra Pasut, Alexandra Pislaru, Aleksander S. Popel, Raymundo A. Quintana, Arshed A. Quyyumi, Francisco J. Rios, Stanley G. Rockson, Martina Rudnicki, Junichi Saito, Charles D. Searles, Timothy W. Secomb, Cristina M. Sena, Richard L. Sidman, Federico Silva-Palacios, Tracey L. Smith, Suman Sood, Laurence S. Sperling, R. Sathish Srinivasan, Kimon Stamatelopoulos, Konstantinos Stellos, Naidi Sun, Wen Tian, Rhian M. Touyz, Nikolaos Ι. Vlachogiannis, Jessica E. Wagenseil, Thomas W. Wakefield, Charlotte R. Wayne, Changhong Xing, Ming Wai Yeung, Yu Zhang, Chen Zhao
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::368f68174074e2f57417a7dd878baa13
https://doi.org/10.1016/b978-0-12-822546-2.01002-9
https://doi.org/10.1016/b978-0-12-822546-2.01002-9
Autor:
Luis Eduardo Juarez-Orozco, Riku Klén, Mikael Niemi, Bram Ruijsink, Gustavo Daquarti, Rene van Es, Jan-Walter Benjamins, Ming Wai Yeung, Pim van der Harst, Juhani Knuuti
Publikováno v:
Current cardiology reportsPapers of particular interest, published recently, have been highlighted as:• Of importance•• Of major importance. 24(4)
Purpose of Review As machine learning-based artificial intelligence (AI) continues to revolutionize the way in which we analyze data, the field of nuclear cardiology provides fertile ground for the implementation of these complex analytics. This revi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d619ac86c8ca1f7e59d79b2c349d759
https://pubmed.ncbi.nlm.nih.gov/35171443
https://pubmed.ncbi.nlm.nih.gov/35171443
Autor:
Sergey V. Nesterov, Emmanuel Deshayes, Luis Eduardo Juarez-Orozco, Robert A. deKemp, Roberto Sciagrà, Simona Malaspina, Leonardo Settimo, Chunlei Han, Darja V. Ryzhkova, Irina S. Kostina, Kilem L. Gwet, John O. Prior, Juhani M. Knuuti
Publikováno v:
Annals of nuclear medicine, vol. 36, no. 6, pp. 507-514
Purpose To estimate the interobserver agreement of the Carimas software package (SP) on global, regional, and segmental levels for the most widely used myocardial perfusion PET tracer—Rb-82. Materials and methods Rest and stress Rb-82 PET scans of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecb7c3adf8c389ca345470b0096acfec
https://pubmed.ncbi.nlm.nih.gov/35192160
https://pubmed.ncbi.nlm.nih.gov/35192160