Zobrazeno 1 - 10
of 2 190
pro vyhledávání: '"Petersen, Steffen"'
Autor:
Skorupko, Grzegorz, Osuala, Richard, Szafranowska, Zuzanna, Kushibar, Kaisar, Aung, Nay, Petersen, Steffen E, Lekadir, Karim, Gkontra, Polyxeni
The progress in deep learning solutions for disease diagnosis and prognosis based on cardiac magnetic resonance imaging is hindered by highly imbalanced and biased training data. To address this issue, we propose a method to alleviate imbalances inhe
Externí odkaz:
http://arxiv.org/abs/2403.19508
Autor:
Lekadir, Karim, Feragen, Aasa, Fofanah, Abdul Joseph, Frangi, Alejandro F, Buyx, Alena, Emelie, Anais, Lara, Andrea, Porras, Antonio R, Chan, An-Wen, Navarro, Arcadi, Glocker, Ben, Botwe, Benard O, Khanal, Bishesh, Beger, Brigit, Wu, Carol C, Cintas, Celia, Langlotz, Curtis P, Rueckert, Daniel, Mzurikwao, Deogratias, Fotiadis, Dimitrios I, Zhussupov, Doszhan, Ferrante, Enzo, Meijering, Erik, Weicken, Eva, González, Fabio A, Asselbergs, Folkert W, Prior, Fred, Krestin, Gabriel P, Collins, Gary, Tegenaw, Geletaw S, Kaissis, Georgios, Misuraca, Gianluca, Tsakou, Gianna, Dwivedi, Girish, Kondylakis, Haridimos, Jayakody, Harsha, Woodruf, Henry C, Mayer, Horst Joachim, Aerts, Hugo JWL, Walsh, Ian, Chouvarda, Ioanna, Buvat, Irène, Tributsch, Isabell, Rekik, Islem, Duncan, James, Kalpathy-Cramer, Jayashree, Zahir, Jihad, Park, Jinah, Mongan, John, Gichoya, Judy W, Schnabel, Julia A, Kushibar, Kaisar, Riklund, Katrine, Mori, Kensaku, Marias, Kostas, Amugongo, Lameck M, Fromont, Lauren A, Maier-Hein, Lena, Alberich, Leonor Cerdá, Rittner, Leticia, Phiri, Lighton, Marrakchi-Kacem, Linda, Donoso-Bach, Lluís, Martí-Bonmatí, Luis, Cardoso, M Jorge, Bobowicz, Maciej, Shabani, Mahsa, Tsiknakis, Manolis, Zuluaga, Maria A, Bielikova, Maria, Fritzsche, Marie-Christine, Camacho, Marina, Linguraru, Marius George, Wenzel, Markus, De Bruijne, Marleen, Tolsgaard, Martin G, Ghassemi, Marzyeh, Ashrafuzzaman, Md, Goisauf, Melanie, Yaqub, Mohammad, Abadía, Mónica Cano, Mahmoud, Mukhtar M E, Elattar, Mustafa, Rieke, Nicola, Papanikolaou, Nikolaos, Lazrak, Noussair, Díaz, Oliver, Salvado, Olivier, Pujol, Oriol, Sall, Ousmane, Guevara, Pamela, Gordebeke, Peter, Lambin, Philippe, Brown, Pieta, Abolmaesumi, Purang, Dou, Qi, Lu, Qinghua, Osuala, Richard, Nakasi, Rose, Zhou, S Kevin, Napel, Sandy, Colantonio, Sara, Albarqouni, Shadi, Joshi, Smriti, Carter, Stacy, Klein, Stefan, Petersen, Steffen E, Aussó, Susanna, Awate, Suyash, Raviv, Tammy Riklin, Cook, Tessa, Mutsvangwa, Tinashe E M, Rogers, Wendy A, Niessen, Wiro J, Puig-Bosch, Xènia, Zeng, Yi, Mohammed, Yunusa G, Aquino, Yves Saint James, Salahuddin, Zohaib, Starmans, Martijn P A
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinica
Externí odkaz:
http://arxiv.org/abs/2309.12325
Autor:
Salih, Ahmed, Raisi-Estabragh, Zahra, Galazzo, Ilaria Boscolo, Radeva, Petia, Petersen, Steffen E., Menegaz, Gloria, Lekadir, Karim
eXplainable artificial intelligence (XAI) methods have emerged to convert the black box of machine learning (ML) models into a more digestible form. These methods help to communicate how the model works with the aim of making ML models more transpare
Externí odkaz:
http://arxiv.org/abs/2305.02012
Autor:
Salih, Ahmed, Galazzo, Ilaria Boscolo, Raisi-Estabragh, Zahra, Petersen, Steffen E., Menegaz, Gloria, Radeva, Petia
Explainable Artificial Intelligence (XAI) provides tools to help understanding how the machine learning models work and reach a specific outcome. It helps to increase the interpretability of models and makes the models more trustworthy and transparen
Externí odkaz:
http://arxiv.org/abs/2304.01717
The Planetary Boundary for Climate Change has been surpassed, and humanity must therefore decide on a pathway back to the safe operating space below the Planetary boundaries to minimise the risk of deleterious or even catastrophic environmental chang
Externí odkaz:
http://arxiv.org/abs/2209.00118
Autor:
Figliozzi, Stefano a, b, c, Di Maio, Silvana a, Georgiopoulos, Georgios d, Vandenberk, Bert e, Chiribiri, Amedeo c, Francone, Marco a, b, Aung, Nay f, Petersen, Steffen E. f, Leiner, Tim g, Bogaert, Jan e, Masci, Pier-Giorgio c, ⁎
Publikováno v:
In Journal of Cardiovascular Magnetic Resonance Summer 2025 27(1)
Autor:
Mariscal-Harana, Jorge, Asher, Clint, Vergani, Vittoria, Rizvi, Maleeha, Keehn, Louise, Kim, Raymond J., Judd, Robert M., Petersen, Steffen E., Razavi, Reza, King, Andrew, Ruijsink, Bram, Puyol-Antón, Esther
Artificial intelligence (AI) techniques have been proposed for automating analysis of short axis (SAX) cine cardiac magnetic resonance (CMR), but no CMR analysis tool exists to automatically analyse large (unstructured) clinical CMR datasets. We deve
Externí odkaz:
http://arxiv.org/abs/2206.08137
Publikováno v:
In Journal of Building Engineering 15 November 2024 97
Autor:
Dashtban, Ashkan, Mizani, Mehrdad A., Pasea, Laura, Tomlinson, Christopher, Mu, Yi, Islam, Nazrul, Rafferty, Sarah, Warren-Gash, Charlotte, Denaxas, Spiros, Horstmanshof, Kim, Kontopantelis, Evangelos, Petersen, Steffen, Sudlow, Cathie, Khunti, Kamlesh, Banerjee, Amitava
Publikováno v:
In International Journal of Infectious Diseases September 2024 146
Autor:
McCracken, Celeste, Condurache, Dorina-Gabriela, Szabo, Liliana, Elghazaly, Hussein, Walter, Fiona M., Mead, Adam J., Chakraverty, Ronjon, Harvey, Nicholas C., Manisty, Charlotte H., Petersen, Steffen E., Neubauer, Stefan, Raisi-Estabragh, Zahra
Publikováno v:
In JACC: CardioOncology August 2024 6(4):575-588