Zobrazeno 1 - 10
of 2 708
pro vyhledávání: '"Steffen, E."'
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
We introduce the concept of a $k$-token signed graph and study some of its combinatorial and algebraic properties. We prove that two switching isomorphic signed graphs have switching isomorphic token graphs. Moreover, we show that the Laplacian spect
Externí odkaz:
http://arxiv.org/abs/2403.02924
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
Autor:
Mihir M. Sanghvi, MBBS, Julia Ramírez, PhD, Sucharitha Chadalavada, MBBS, Nay Aung, MBBS, PhD, Patricia B. Munroe, PhD, Nikolaos Donos, DDS, PhD, Steffen E. Petersen, MD, DPhil
Publikováno v:
JACC: Advances, Vol 3, Iss 10, Pp 101241- (2024)
Background: Periodontal disease is the sixth most common disease worldwide and may be a contributory risk factor for cardiovascular disease (CVD). Objectives: This study utilizes noninvasive cardiac imaging and longitudinal and genetic data to charac
Externí odkaz:
https://doaj.org/article/e3329572a96b4055b908fbea951b76de
Autor:
Vijay Shyam-Sundar, Daniel Harding, Abbas Khan, Musa Abdulkareem, Greg Slabaugh, Saidi A. Mohiddin, Steffen E. Petersen, Nay Aung
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 11 (2024)
Myocarditis is a cardiovascular disease characterised by inflammation of the heart muscle which can lead to heart failure. There is heterogeneity in the mode of presentation, underlying aetiologies, and clinical outcome with impact on a wide range of
Externí odkaz:
https://doaj.org/article/106a131adf4948f0bd671951d6b2d8da
Autor:
Künzel, Steffen E.1 (AUTHOR) payam.kabiri@charite.de, Kabiri, Payam1 (AUTHOR), zur Bonsen, Lynn1 (AUTHOR), Frentzel, Dominik P.1 (AUTHOR), Böker, Alexander1 (AUTHOR), Joussen, Antonia M.1 (AUTHOR), Zeitz, Oliver1 (AUTHOR)
Publikováno v:
Journal of Clinical Medicine. Aug2024, Vol. 13 Issue 15, p4359. 13p.
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