Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Sara, Andresen"'
Autor:
Sara Andresen, Suraj Balakrishna, Catrina Mugglin, Axel J Schmidt, Dominique L Braun, Alex Marzel, Thanh Doco Lecompte, Katharine Ea Darling, Jan A Roth, Patrick Schmid, Enos Bernasconi, Huldrych F Günthard, Andri Rauch, Roger D Kouyos, Luisa Salazar-Vizcaya, Swiss HIV Cohort Study
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 10, p e1010559 (2022)
Machine learning is increasingly introduced into medical fields, yet there is limited evidence for its benefit over more commonly used statistical methods in epidemiological studies. We introduce an unsupervised machine learning framework for longitu
Externí odkaz:
https://doaj.org/article/f992a8fc624841ee883b35f5b3a5042d
Autor:
Burcu Tepekule, Anthony Hauser, Viacheslav N Kachalov, Sara Andresen, Thomas Scheier, Peter W Schreiber, Huldrych F Günthard, Roger D Kouyos
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 1, p e1008609 (2021)
A key parameter in epidemiological modeling which characterizes the spread of an infectious disease is the generation time, or more generally the distribution of infectiousness as a function of time since infection. There is increasing evidence suppo
Externí odkaz:
https://doaj.org/article/bb8d99f4d80b4b2fb33932662eaad2aa
Autor:
Sara, Andresen, Suraj, Balakrishna, Catrina, Mugglin, Axel J, Schmidt, Dominique L, Braun, Alex, Marzel, Thanh, Doco Lecompte, Katharine Ea, Darling, Jan A, Roth, Patrick, Schmid, Enos, Bernasconi, Huldrych F, Günthard, Andri, Rauch, Roger D, Kouyos, Luisa, Salazar-Vizcaya
Publikováno v:
PLoS computational biology. 18(10)
Machine learning is increasingly introduced into medical fields, yet there is limited evidence for its benefit over more commonly used statistical methods in epidemiological studies. We introduce an unsupervised machine learning framework for longitu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::728eabad33dd42ad3ff68a7b50f44b8e
https://pubmed.ncbi.nlm.nih.gov/36302041
https://pubmed.ncbi.nlm.nih.gov/36302041