Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
Nenad Tomašev(Google DeepMind (United Kingdom)), Natalie Harris(Google (United Kingdom)), Sebastien Baur(Google (United Kingdom)), Anne Mottram(Google DeepMind (United Kingdom)), Xavier Glorot(Google DeepMind (United Kingdom)), Jack W. Rae(Google DeepMind (United Kingdom)), Michał Zieliński(Google DeepMind (United Kingdom)), Harry Askham(Google DeepMind (United Kingdom)), André Saraiva(Google DeepMind (United Kingdom)), Valerio Magliulo(Google (United Kingdom)), Clemens Meyer(Google DeepMind (United Kingdom)), Suman Ravuri(Google DeepMind (United Kingdom)), Ivan Protsyuk(Google (United Kingdom)), Alistair Connell(Google (United Kingdom)), Cían Hughes(Google (United Kingdom)), Alan Karthikesalingam(Google (United Kingdom)), Julien Cornebise(Google DeepMind (United Kingdom)), Hugh Montgomery(University College London), Geraint Rees(University College London), Chris Laing(Royal London Hospital), Clifton R. Baker, Thomas F. Osborne(VA Palo Alto Health Care System), Ruth Reeves, Demis Hassabis(Google DeepMind (United Kingdom)), Dominic King(Google (United Kingdom)), Mustafa Suleyman(Google DeepMind (United Kingdom)), Trevor Back(Google DeepMind (United Kingdom)), Christopher Nielson(University of Nevada, Las Vegas), Martin Seneviratne(Google (United Kingdom)), Joseph R. Ledsam(Google (United States)), Shakir Mohamed(Google DeepMind (United Kingdom))
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