Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Valerio Magliulo"'
Autor:
Ivan Protsyuk, Martin G. Seneviratne, Andre Saraiva, Natalie Harris, Hugh Montgomery, Mustafa Suleyman, Xavier Glorot, Dominic King, Jack W. Rae, Clifton R. Baker, Alistair Connell, Suman V. Ravuri, Trevor Back, Clemens Meyer, Nenad Tomasev, Harry Askham, Michal Zielinski, Ruth M. Reeves, Joseph R. Ledsam, Shakir Mohamed, Thomas F. Osborne, Cian Hughes, Chris Laing, Alan Karthikesalingam, Valerio Magliulo, Anne Mottram, Christopher Nielson, Sebastien Baur, Julien Cornebise, Demis Hassabis, Geraint Rees
Publikováno v:
Nature Protocols. 16:2765-2787
Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electron
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1547705a8f9b73ddd1995e08dd7f633d
https://doi.org/10.1038/s41596-021-00513-5
https://doi.org/10.1038/s41596-021-00513-5
Autor:
Nenad, Tomašev, Natalie, Harris, Sebastien, Baur, Anne, Mottram, Xavier, Glorot, Jack W, Rae, Michal, Zielinski, Harry, Askham, Andre, Saraiva, Valerio, Magliulo, Clemens, Meyer, Suman, Ravuri, Ivan, Protsyuk, Alistair, Connell, Cían O, Hughes, Alan, Karthikesalingam, Julien, Cornebise, Hugh, Montgomery, Geraint, Rees, Chris, Laing, Clifton R, Baker, Thomas F, Osborne, Ruth, Reeves, Demis, Hassabis, Dominic, King, Mustafa, Suleyman, Trevor, Back, Christopher, Nielson, Martin G, Seneviratne, Joseph R, Ledsam, Shakir, Mohamed
Publikováno v:
Nature protocols. 16(6)
Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electron
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::b6eee043792243fcb4afed951517d636
https://pubmed.ncbi.nlm.nih.gov/33953393
https://pubmed.ncbi.nlm.nih.gov/33953393