Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Rudi Agius"'
Autor:
Rudi Agius, Anders C. Riis-Jensen, Bettina Wimmer, Caspar da Cunha-Bang, Daniel Dawson Murray, Christian Bjorn Poulsen, Marianne B. Bertelsen, Berit Schwartz, Jens Dilling Lundgren, Henning Langberg, Carsten Utoft Niemann
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Research algorithms are seldom externally validated or integrated into clinical practice, leaving unknown challenges in deployment. In such efforts, one needs to address challenges related to data harmonization, the performance of an algorit
Externí odkaz:
https://doaj.org/article/26a0ab71dbb944109353ae6a7c63a277
Autor:
Rebecka Svanberg, Cameron MacPherson, Adrian Zucco, Rudi Agius, Tereza Faitova, Michael Asger Andersen, Caspar da Cunha-Bang, Lars Klingen Gjærde, Maria Elizabeth Engel Møller, Patrick Terrence Brooks, Birgitte Lindegaard, Adin Sejdic, Anne Ortved Gang, Ditte Stampe Hersby, Christian Brieghel, Susanne Dam Nielsen, Daria Podlekareva, Annemette Hald, Jakob Thaning Bay, Hanne Marquart, Jens Lundgren, Anne-Mette Lebech, Marie Helleberg, Carsten Utoft Niemann, Sisse Rye Ostrowski
Publikováno v:
Communications Medicine, Vol 2, Iss 1, Pp 1-15 (2022)
Svanberg et al. longitudinally assess the immune response in patients with COVID-19. The authors report specific immune parameters associated with the development of severe disease.
Externí odkaz:
https://doaj.org/article/bd613745fba3483e88dcd4c9630cbdab
Autor:
Carsten Niemann, Mark-David Levin, Anders Österborg, Jeanette Lundin, Magdalena Kättström, Jeanette Vollerup, Caspar Da Cunha-Bang, Michael Foraux, Christian Brieghel, Fransien de Boer, Lisbeth Enggaard, Christian Bjorn Poulsen, Joanne Reekie, Rudi Agius
Publikováno v:
HemaSphere, Vol 7, p e1432517 (2023)
Externí odkaz:
https://doaj.org/article/846c0a984fc74588a41972a7a107bbcc
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Autor:
Adrian G. Zucco, Rudi Agius, Rebecka Svanberg, Kasper S. Moestrup, Ramtin Z. Marandi, Cameron Ross MacPherson, Jens Lundgren, Sisse R. Ostrowski, Carsten U. Niemann
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract Interpretable risk assessment of SARS-CoV-2 positive patients can aid clinicians to implement precision medicine. Here we trained a machine learning model to predict mortality within 12 weeks of a first positive SARS-CoV-2 test. By leveragin
Externí odkaz:
https://doaj.org/article/ab4930ae24b141eaa08fd86ddee41197
Autor:
Rebecka Svanberg, Cameron MacPherson, Adrian Zucco, Rudi Agius, Tereza Faitova, Michael Asger Andersen, Caspar da Cunha-Bang, Lars Klingen Gjærde, Maria Elizabeth Engel Møller, Patrick Terrence Brooks, Birgitte Lindegaard, Adin Sejdic, Zitta Barrella Harboe, Anne Ortved Gang, Ditte Stampe Hersby, Christian Brieghel, Susanne Dam Nielsen, Daria Podlekareva, Annemette Hald, Jakob Thaning Bay, Hanne Marquart, Jens Lundgren, Anne-Mette Lebech, Marie Helleberg, Carsten Utoft Niemann, Sisse Rye Ostrowski
Publikováno v:
Communications Medicine, Vol 3, Iss 1, Pp 1-2 (2023)
Externí odkaz:
https://doaj.org/article/07731d18f44f4954a5091a4bb6c191d6
Autor:
Rudi Agius, Christian Brieghel, Michael A. Andersen, Alexander T. Pearson, Bruno Ledergerber, Alessandro Cozzi-Lepri, Yoram Louzoun, Christen L. Andersen, Jacob Bergstedt, Jakob H. von Stemann, Mette Jørgensen, Man-Hung Eric Tang, Magnus Fontes, Jasmin Bahlo, Carmen D. Herling, Michael Hallek, Jens Lundgren, Cameron Ross MacPherson, Jan Larsen, Carsten U. Niemann
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Chronic lymphocytic leukemia is an indolent disease, and many patients succumb to infection rather than the direct effects of the disease. Here, the authors use medical records and machine learning to predict the patients that may be at risk of infec
Externí odkaz:
https://doaj.org/article/d34aa0eace4042dc8ea0d505bfcb57d5
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 9, p e1003216 (2013)
Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated o
Externí odkaz:
https://doaj.org/article/9360f627a0cb4c389279edc2a1239541
Publikováno v:
Parviz, M, Brieghel, C, Agius, R & Niemann, C U 2022, ' Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data ', Blood advances, vol. 6, no. 12, pp. 3716-3728 . https://doi.org/10.1182/bloodadvances.2021006351
A highly variable clinical course, immune dysfunction, and a complex genetic blueprint pose challenges for treatment decisions and the management of risk of infection in patients with chronic lymphocytic leukemia (CLL). In recent years, the use of ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b47689f67f42dcd302f6d588792384e8
https://doi.org/10.1182/bloodadvances.2021006351
https://doi.org/10.1182/bloodadvances.2021006351
Publikováno v:
Leukemia & Lymphoma. 63:265-278
Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation of these advances to the patient's bedside for AI assisted interventions is not yet the norm. With
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::534089fd200af5388b9a43611c68a209
https://doi.org/10.1080/10428194.2021.1973672
https://doi.org/10.1080/10428194.2021.1973672
Autor:
Mehdi Parviz, Rudi Agius, Emelie Curovic Rotbain, Kathrine Aarup, Noomi Vainer, Carsten Utoft Niemann
Publikováno v:
Blood. 140:7034-7035
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc85a52eef6d5eb135af1cd850e7324f
https://doi.org/10.1182/blood-2022-158505
https://doi.org/10.1182/blood-2022-158505