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Katie Tucker

Guy's and St Thomas' NHS Foundation Trust

London

United Kingdom

King’s College London

Strand

London, England WC2R 2LS

United Kingdom

SCHOLARLY PAPERS

3

DOWNLOADS

304

TOTAL CITATIONS

0

Scholarly Papers (3)

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1.

Predicting Hospital Outpatient Attendance Using Random Forest Classifiers

Number of pages: 17 Posted: 05 May 2021
Jonathan Holdship, Harpreet Dhanoa, Adrian Hopper, Claire J. Steves, Mark Butler, Ingrid Wolfe, Katie Tucker, Katie Tucker, Carolyn Cooper, Jeremy Yates and Jeremy Yates
Guy's and St Thomas' NHS Foundation Trust, Guy's and St Thomas' NHS Foundation Trust, NHS England and NHS Improvement - Getting It Right First Time Programme, Guy's and St Thomas' NHS Foundation Trust, Guy's and St Thomas' NHS Foundation Trust, King’s College London - Department of Women and Children’s Health, Guy's and St Thomas' NHS Foundation TrustKing’s College London, Guy's and St Thomas' NHS Foundation Trust and University College London - Department of Computer ScienceScience and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility
Downloads 139 (530,816)

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2.

The Relationship Between Frailty, Comorbidity and COVID-19 Mortality in Older COVID-19 Patients: Analysis of an Administrative Dataset Using Machine Learning Techniques

Number of pages: 28 Posted: 16 Sep 2021
Johannes Heyl, Flavien Hardy, Katie Tucker, Katie Tucker, Adrian Hopper, Maria J.M. Marchã, Annakan Victor Navaratnam, Tim W.R. Briggs, Jeremy Yates, Jeremy Yates, Jamie Day, Andrew Wheeler, Sue Eve-Jones and William Keith Gray
NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, Guy's and St Thomas' NHS Foundation TrustKing’s College London, NHS England and NHS Improvement - Getting It Right First Time Programme, Science and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, University College London - Department of Computer ScienceScience and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme and NHS England and NHS Improvement - Getting It Right First Time Programme
Downloads 92 (730,864)

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COVID-19, coronavirus, frailty, comorbidity, mortality

3.

Estimating Nosocomial Infection and its Outcomes in Hospital Patients in England with a Diagnosis of COVID-19 Using Machine Learning

Number of pages: 32 Posted: 20 Sep 2021
Flavien Hardy, Johannes Heyl, Katie Tucker, Katie Tucker, Adrian Hopper, Maria J.M. Marchã, Annakan Victor Navaratnam, Tim W.R. Briggs, Jeremy Yates, Jeremy Yates, Jamie Day, Andrew Wheeler, Sue Eve-Jones and William Keith Gray
NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, Guy's and St Thomas' NHS Foundation TrustKing’s College London, NHS England and NHS Improvement - Getting It Right First Time Programme, Science and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, University College London - Department of Computer ScienceScience and Technology Facilities Council Distributed Research Utilising Advanced Computing High Performance Computing Facility, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme, NHS England and NHS Improvement - Getting It Right First Time Programme and NHS England and NHS Improvement - Getting It Right First Time Programme
Downloads 73 (852,604)

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COVID-19, coronavirus, mortality, hospital acquired infection, nosocomial infection