Reference Architectures for H2O.ai

Unleash the power of AI using H2O.ai on Dell EMC infrastructure optimized for machine learning

NVIDIA AND H2O

GPU-ACCELERATED MACHINE

LEARNING

Preliminary risk analysis of 2019 novel coronavirus spread within and beyond China

Shengjie Lai1*, Isaac I. Bogoch2, Alexander Watts3,4, Kamran Khan2,3,4, Zhongjie Li5,

Andrew Tatem1*

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1 WorldPop, School of Geography and Environmental Science, University of

Southampton, UK

2 Department of Medicine, University of Toronto, Toronto, Canada

3 Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada

4 Bluedot, Toronto, Canada

5 Division of Infectious Diseases, Chinese Centre for Disease Control and Prevention

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Transforming Big Data into Timely Insights During Epidemic Emergencies

2nd OIE Global Conference on Biological Threat Reduction

Kamran Khan MD, MPH, FRCPC, Founder, BlueDot

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Associate Professor, Division of Infectious Diseases, University of Toronto

Clinician-Scientist, Li Ka Shing Knowledge Institute, St. Michael’s Hospital

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Transcriptome-wide characterization of human cytomegalovirus in natural infection and experimental latency

Shu Chenga,1, Katie Cavinessa,b,2, Jason Buehlera, Megan Smitheyc,d, Janko Nikolich-Žugicha,c,d,

and Felicia Goodruma,b,c,d,1

The use and reporting of airline passenger data for infectious disease modelling: a systematic review

Margaux Marie Isabelle Meslé1,2, Ian Melvyn Hall1,3,4,5, Robert Matthew Christley1,2, Steve Leach1,4,5,6, Jonathan Michael Read1,2,7

1. National Institute for Health Research, Health Protection Research Unit in Emerging and Zoonotic Infections at University of

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Liverpool, Liverpool, United Kingdom

2. Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom

3. School of Mathematics, University of Manchester, Manchester, United Kingdom

4. Emergency Response Department, Public Health England, Salisbury, United Kingdom

5. National Institute for Health Research, Health Protection Research Unit in Emergency Preparedness and Response at Kings

College London, London, United Kingdom

6. National Institute for Health Research, Health Protection Research Unit in Modelling Methodology at Imperial College London,

London, United Kingdom

7. Centre for Health Informatics Computation and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United

Kingdom

Correspondence: Jonathan Read (jonathan.read@lancs.ac.uk)

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Infectious disease implications of large-scale migration of Venezuelan nationals

Ashleigh R. Tuite, PhD1,2,3*, Andrea Thomas-Bachli, MSc1,2, Hernan Acosta, MD1,2,

Deepit Bhatia, MPH1,2, Carmen Huber, BA1,2, Kieran Petrasek, BA1,2, Alexander Watts,

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PhD1,2, Jean H.E. Yong, MASc1,2, Isaac I. Bogoch, MD4,5, and Kamran Khan, MD1,2,4

1Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada, 2BlueDot, Toronto, Canada, 3Dalla Lana

School of Public Health, University of Toronto, Toronto, Canada, 4Department of Medicine, Division of Infectious

Diseases, University of Toronto, Toronto, Canada and 5Divisions of General Internal Medicine and Infectious Diseases,

University Health Network, Toronto, Canada

*To whom correspondence should be addressed. Ashleigh Tuite, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, Toronto,

Ontario M5B 1T8, Canada; Email: ashleigh.tuite@utoronto.ca

Submitted 30 June 2018; Revised 21 August 2018; Editorial decision 23 August 2018; Accepted 4 September 2018

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Interconnected and Interdependent

Anticipating Infectious Disease Risks in an Increasingly Mobile World

ACRP Insight Event

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March 6th 2018

Associate Professor

Faculty of Medicine

Dalla Lana School of Public Health

University of Toronto

Kamran Khan MD, MPH

Division of Infectious Diseases

St. Michael’s Hospital

Founder, BlueDot

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