Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kimberly Amador"'
Autor:
Milton Camacho, Matthias Wilms, Hannes Almgren, Kimberly Amador, Richard Camicioli, Zahinoor Ismail, Oury Monchi, Nils D. Forkert, For the Alzheimer’s Disease Neuroimaging Initiative
Publikováno v:
npj Parkinson's Disease, Vol 10, Iss 1, Pp 1-12 (2024)
Abstract Parkinson’s disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop an
Externí odkaz:
https://doaj.org/article/8da5db4b61c5422fab5a52810c745b6f
Autor:
Thomas Renson, Nils D. Forkert, Kimberly Amador, Paivi Miettunen, Simon J. Parsons, Muhammed Dhalla, Nicole A. Johnson, Nadia Luca, Heinrike Schmeling, Rebeka Stevenson, Marinka Twilt, Lorraine Hamiwka, Susanne Benseler
Publikováno v:
Pediatric Rheumatology Online Journal, Vol 21, Iss 1, Pp 1-11 (2023)
Abstract Background Multisystem inflammatory syndrome in children (MIS-C) is a severe disease with an unpredictable course and a substantial risk of cardiogenic shock. Our objectives were to (a) compare MIS-C phenotypes across the COVID-19 pandemic,
Externí odkaz:
https://doaj.org/article/cea2671496074b68a89be8866dbcb1e8
Autor:
Anthony J. Winder, Matthias Wilms, Kimberly Amador, Fabian Flottmann, Jens Fiehler, Nils D. Forkert
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Predicting follow-up lesions from baseline CT perfusion (CTP) datasets in acute ischemic stroke patients is important for clinical decision making. Deep convolutional networks (DCNs) are assumed to be the current state-of-the-art for this task. Howev
Externí odkaz:
https://doaj.org/article/a46cd338126a4360ad24dcb233f2e99f
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164361
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4caed391700284a62b84bbe7343ba621
https://doi.org/10.1007/978-3-031-16437-8_62
https://doi.org/10.1007/978-3-031-16437-8_62
Publikováno v:
Medical Image Analysis. 82:102610
For the diagnosis and precise treatment of acute ischemic stroke, predicting the final location and volume of lesions is of great clinical interest. Current deep learning-based prediction methods mainly use perfusion parameter maps, which can be calc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4c4b10fe33848e0b38999349a8bb2e9
https://doi.org/10.1016/j.media.2022.102610
https://doi.org/10.1016/j.media.2022.102610
Autor:
Kimberly Amador, Anthony Winder, Nils D. Forkert, Jasmine A. Moore, Alejandro P. Gutierrez, Jordan J. Bannister, Anup Tuladhar, Nanjia Wang, Deepthi Rajashekar, Pauline Mouches, Serena Schimert, Nagesh K. Subbanna, Lucas Lo Vercio, Matthias Wilms, Sebastian Crites, M. Ethan MacDonald
Publikováno v:
Journal of Neural Engineering. 17:062001
In an increasingly data-driven world, artificial intelligence is expected to be a key tool for converting big data into tangible benefits and the healthcare domain is no exception to this. Machine learning aims to identify complex patterns in multi-d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cd5e17cebe310c3e74a020a24674707
https://doi.org/10.1088/1741-2552/abbff2
https://doi.org/10.1088/1741-2552/abbff2