Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Cameron Ross MacPherson"'
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:
Ramtin Zargari Marandi, Preston Leung, Chathurani Sigera, Daniel Dawson Murray, Praveen Weeratunga, Deepika Fernando, Chaturaka Rodrigo, Senaka Rajapakse, Cameron Ross MacPherson
Publikováno v:
PLoS Neglected Tropical Diseases, Vol 17, Iss 3, p e0010758 (2023)
BackgroundAt least a third of dengue patients develop plasma leakage with increased risk of life-threatening complications. Predicting plasma leakage using laboratory parameters obtained in early infection as means of triaging patients for hospital a
Externí odkaz:
https://doaj.org/article/2f6ace7c13724425818e57d6c7ba35d8
Autor:
Kirstine K. Rasmussen, Quenia dos Santos, Cameron Ross MacPherson, Adrian G. Zucco, Lars Klingen Gjærde, Emma E. Ilett, Isabelle Lodding, Marie Helleberg, Jens D. Lundgren, Susanne D. Nielsen, Susanne Brix, Henrik Sengeløv, Daniel D. Murray
Publikováno v:
Metabolites, Vol 13, Iss 9, p 968 (2023)
Immune dysfunction resulting from allogeneic haematopoietic stem cell transplantation (aHSCT) predisposes one to an elevated risk of cytomegalovirus (CMV) infection. Changes in metabolism have been associated with adverse outcomes, and in this study,
Externí odkaz:
https://doaj.org/article/c0f19a57aa95435990307037ca22b5cd
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
Autor:
Ramtin Zargari Marandi, Mette Jørgensen, Emma Elizabeth Ilett, Jens Christian Nørgaard, Marc Noguera-Julian, Roger Paredes, Jens D. Lundgren, Henrik Sengeløv, Cameron Ross MacPherson
Publikováno v:
Cells, Vol 11, Iss 24, p 4089 (2022)
Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association mig
Externí odkaz:
https://doaj.org/article/4d2c300b8e78426195ee2cf9f8ad40e0
Autor:
Mette Jørgensen, Jens C. Nørgaard, Emma E. Ilett, Ramtin Z. Marandi, Marc Noguera-Julian, Roger Paredes, Daniel D. Murray, Jens Lundgren, Cameron Ross MacPherson, Henrik Sengeløv
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 19, p 11115 (2022)
Allogeneic hematopoietic stem cell transplantation (aHSCT) is a putative curative treatment for malignant hematologic disorders. During transplantation, the immune system is suppressed/eradicated through a conditioning regimen (non-myeloablative or m
Externí odkaz:
https://doaj.org/article/d52d39ab6a0543349336e38cc011ebe9
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Autor:
Ramtin Z. Marandi, Carsten Utoft Niemann, Sisse R. Ostrowski, Rudi Agius, Cameron Ross MacPherson, Rebecka Svanberg, Jens D Lundgren, Kasper Sommerlund Moestrup, Adrian G. Zucco
Publikováno v:
Zucco, A G, Agius, R, Svanberg, R, Moestrup, K S, Marandi, R Z, MacPherson, C R, Lundgren, J, Ostrowski, S R & Niemann, C U 2022, ' Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning ', Scientific Reports, vol. 12, 13879 . https://doi.org/10.1038/s41598-022-17953-y
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 leveraging data on
Autor:
Cameron Ross MacPherson, Virginia L. Kan, Shweta Sharma, Adrian G. Zucco, Christina Ekenberg, Joanne Reekie, Daniel D Murray, James D. Neaton, Jens D Lundgren, H. Clifford Lane, Abdel Babiker, Smart Study Groups Insight Start
Publikováno v:
AIDS
Ekenberg, C, Reekie, J, Zucco, A G, Murray, D D, Sharma, S, Macpherson, C R, Babiker, A, Kan, V, Lane, H C, Neaton, J D, Lundgren, J D & INSIGHT START, SMART Study Groups 2021, ' The association of human leukocyte antigen alleles with clinical disease progression in HIV-positive cohorts with varied treatment strategies ', AIDS, vol. 35, no. 5, pp. 783-789 . https://doi.org/10.1097/QAD.0000000000002800
Ekenberg, C, Reekie, J, Zucco, A G, Murray, D D, Sharma, S, Macpherson, C R, Babiker, A, Kan, V, Lane, H C, Neaton, J D, Lundgren, J D & INSIGHT START, SMART Study Groups 2021, ' The association of human leukocyte antigen alleles with clinical disease progression in HIV-positive cohorts with varied treatment strategies ', AIDS, vol. 35, no. 5, pp. 783-789 . https://doi.org/10.1097/QAD.0000000000002800
OBJECTIVES: The Strategic Timing of AntiRetroviral Treatment (START) and Strategies for Management of Antiretroviral Therapy (SMART) trials demonstrated that ART can partly reverse clinically defined immune dysfunction induced by HIV replication. As
Autor:
Daniel D Murray, Gedske Daugaard, Mette Jørgensen, Joanne Reekie, Roger Paredes, Cameron Ross MacPherson, Jens Christian Nørgaard, Henrik Sengeløv, Jens D Lundgren, Emma E Ilett, Marie Helleberg, Marc Noguera-Julian
Publikováno v:
Ilett, E E, Jørgensen, M, Noguera-Julian, M, Nørgaard, J C, Daugaard, G, Helleberg, M, Paredes, R, Murray, D D, Lundgren, J, MacPherson, C, Reekie, J & Sengeløv, H 2020, ' Associations of the gut microbiome and clinical factors with acute GVHD in allogeneic HSCT recipients ', Blood advances, vol. 4, no. 22, pp. 5797-5809 . https://doi.org/10.1182/bloodadvances.2020002677
Blood Adv
Blood Adv
Acute graft-versus-host disease (aGVHD) is a leading cause of transplantation-related mortality after allogeneic hematopoietic stem cell transplantation (aHSCT). 16S ribosomal RNA (16S rRNA) gene-based studies have reported that lower gut bacterial d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50a74a441a2a4c4d3c33d7cd382db9f5
https://curis.ku.dk/portal/da/publications/associations-of-the-gut-microbiome-and-clinical-factors-with-acute-gvhd-in-allogeneic-hsct-recipients(106552ca-dfe1-41b9-9cc7-b45e4f478ded).html
https://curis.ku.dk/portal/da/publications/associations-of-the-gut-microbiome-and-clinical-factors-with-acute-gvhd-in-allogeneic-hsct-recipients(106552ca-dfe1-41b9-9cc7-b45e4f478ded).html
Autor:
Jakob Hjorth von Stemann, Christian Brieghel, Bruno Ledergerber, Christen Lykkegaard Andersen, Michael A. E. Andersen, Jasmin Bahlo, Cameron Ross MacPherson, Alexander T. Pearson, Jens D Lundgren, Magnus Fontes, Rudi Agius, Michael Hallek, Man-Hung Eric Tang, Carsten Utoft Niemann, Jan Larsen, Jacob Bergstedt, Mette Rose Jørgensen, Yoram Louzoun, Carmen D. Herling, Alessandro Cozzi-Lepri
Publikováno v:
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop