Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Harry, Askham"'
Autor:
Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch, Ruheena Mendes, Michelle Livne, Jeffrey De Fauw, Yojan Patel, Clemens Meyer, Harry Askham, Bernadino Romera-Paredes, Christopher Kelly, Alan Karthikesalingam, Carlton Chu, Dawn Carnell, Cheng Boon, Derek D'Souza, Syed Ali Moinuddin, Bethany Garie, Yasmin McQuinlan, Sarah Ireland, Kiarna Hampton, Krystle Fuller, Hugh Montgomery, Geraint Rees, Mustafa Suleyman, Trevor Back, Cían Owen Hughes, Joseph R Ledsam, Olaf Ronneberger
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 7, p e26151 (2021)
BackgroundOver half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This plann
Externí odkaz:
https://doaj.org/article/9f11f2c502c14834af5677c6e22c37ac
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:
Reena Chopra, Jim Winkens, Geraint Rees, Jason Yim, Gabriella Moraes, Trevor Back, Annette Obika, Clemens Meyer, Pearse A. Keane, Marc Wilson, Jeffrey De Fauw, Jonathan Mark Dixon, Marko Lukic, Harry Askham, Katrin Fasler, Joseph R. Ledsam, Terry Spitz, Mustafa Suleyman, Josef Huemer, Cian Hughes, Christopher Kelly, Alan Karthikesalingam, Dominic King, Peng T. Khaw, Demis Hassabis
Publikováno v:
Nature Medicine. 26:892-899
Progression to exudative 'wet' age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbc51f346429a271c52d2de98ba8f2c8
https://doi.org/10.1038/s41591-020-0867-7
https://doi.org/10.1038/s41591-020-0867-7
Autor:
Hugh Montgomery, Alan Karthikesalingam, Xavier Glorot, Christopher Nielson, Harry Askham, Suman V. Ravuri, Trevor Back, Joseph R. Ledsam, Michal Zielinski, Kelly S. Peterson, Geraint Rees, Alistair Connell, Nenad Tomasev, Julien Cornebise, Ivan Protsyuk, Andre Saraiva, Demis Hassabis, Cian Hughes, Chris Laing, Ruth M. Reeves, Shakir Mohamed, Dominic King, Anne Mottram, Jack W. Rae, Mustafa Suleyman, Clemens Meyer, Clifton R. Baker
Publikováno v:
Nature
The early prediction of deterioration could have an important role in supporting healthcare professionals, as an estimated 11% of deaths in hospital follow a failure to promptly recognize and treat deteriorating patients1. To achieve this goal requir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3716eea45fa33fb37c38efb1a54cdd0
https://doi.org/10.1038/s41586-019-1390-1
https://doi.org/10.1038/s41586-019-1390-1
Autor:
Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch, Ruheena Mendes, Michelle Livne, Jeffrey De Fauw, Yojan Patel, Clemens Meyer, Harry Askham, Bernadino Romera-Paredes, Christopher Kelly, Alan Karthikesalingam, Carlton Chu, Dawn Carnell, Cheng Boon, Derek D'Souza, Syed Ali Moinuddin, Bethany Garie, Yasmin McQuinlan, Sarah Ireland, Kiarna Hampton, Krystle Fuller, Hugh Montgomery, Geraint Rees, Mustafa Suleyman, Trevor Back, Cían Owen Hughes, Joseph R Ledsam, Olaf Ronneberger
BACKGROUND Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This plan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76b8fba36c05059b31342ecce43c0f2c
https://doi.org/10.2196/preprints.26151
https://doi.org/10.2196/preprints.26151
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
Autor:
Kareem Ayoub, Trevor Back, Rosalind Raine, Alan Karthikesalingam, Pearse A. Keane, Xavier Glorot, Hugh Montgomery, Julien Cornebise, Demis Hassabis, Daniel Visentin, Brendan O'Donoghue, Adnan Tufail, Catherine A Egan, Jeffrey De Fauw, Olaf Ronneberger, Peng T. Khaw, Harry Askham, Reena Chopra, Faith Mackinder, Joseph R. Ledsam, Dominic King, Nenad Tomasev, Julian Hughes, Simon Bouton, Clemens Meyer, George van den Driessche, Cian Hughes, Stanislav Nikolov, Mustafa Suleyman, Balaji Lakshminarayanan, Dawn A Sim, Bernardino Romera-Paredes, Sam Blackwell, Geraint Rees
Publikováno v:
Nature Medicine. 24:1342-1350
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common disease
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45a19e5177294bdc580995357abe336e
https://doi.org/10.1038/s41591-018-0107-6
https://doi.org/10.1038/s41591-018-0107-6
Autor:
Cían Owen Hughes, Harry Askham, Joseph R. Ledsam, Jeffrey De Fauw, Mustafa Suleyman, Kiarna Hampton, Cheng Boon, Carlton Chu, Clemens Meyer, Yojan Patel, Yasmin McQuinlan, Bernadino Romera-Paredes, Krystle Fuller, R. Mendes, S. Moinuddin, Stanislav Nikolov, Sarah Ireland, Derek D'Souza, Olaf Ronneberger, Trevor Back, Christopher Kelly, Michelle Livne, Bethany Garie, Dawn Carnell, Alan Karthikesalingam, Hugh Montgomery, Alexei Zverovitch, Geraint Rees, Sam Blackwell
Publikováno v:
Journal of Medical Internet Research
Background Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This plan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65807baa63c6be419fb27ce0c33c1bf2
https://doi.org/10.2196/26151
https://doi.org/10.2196/26151
Autor:
Ivan Protsyuk, Xavier Glorot, Christopher Nielson, Alistair Connell, Cian Hughes, Shakir Mohamed, Chris Laing, Julien Cornebise, Andre Saraiva, Ruth M. Reeves, Demis Hassabis, Alan Karthikesalingam, Hugh Montgomery, Jack W. Rae, Clemens Meyer, Dominic King, Mustafa Suleyman, Suman V. Ravuri, Michal Zielinski, Anne Mottram, Harry Askham, Geraint Rees, Joseph R. Ledsam, Clifton R. Baker, Nenad Tomasev, Kelly S. Peterson, Trevor Back
Early detection of patient deterioration is key to unlocking the potential for targeted preventative care and improving patient outcomes. This protocol describes a workflow for developing deep learning continuous risk models for early prediction of f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca81db07e34dd4c756362e089da89768
https://doi.org/10.21203/rs.2.10083/v1
https://doi.org/10.21203/rs.2.10083/v1
Publikováno v:
WebSci
L-LDA is a new supervised topic model for assigning "topics" to a collection of documents (e.g., Twitter profiles). User studies have shown that L-LDA effectively performs a variety of tasks in Twitter that include not only assigning topics to profil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ede2be391ad21754c5e14868188481ce
https://doi.org/10.1145/2380718.2380750
https://doi.org/10.1145/2380718.2380750