Simon Ball

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Honorary Professor

University of Birmingham

United Kingdom

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About

Simon Ball is an Honorary Professor at the University of Birmingham, UK. His research areas focus on clinical decision support systems, electronic health records, and the application of machine learning in healthcare. He has published on topics such as the adoption of electronic order communications in NHS secondary care and how machine learning of COVID-19 clinical data can identify therapeutic population structures. His work aims to enhance patient care and outcomes through the integration of technology in clinical settings.

Recent Grants

Grant: Close

DARE: Creating the blueprint for a federated network of next generation, cross-council Trusted Research Environments.

Open Date: 2022-01-04

Close Date: 2022-08-30

Grant: Close

Multimorbidity Mechanism and Therapeutics Research Collaborative

Open Date: 2021-03-22

Close Date: 2024-03-21

Grant: Close

ISCF HDRUK DIH Sprint Exemplar: A scalable federated solution for UK health data encryption, linking and discovery

Open Date: 2019-02-01

Close Date: 2020-03-30

Grant: Close

Midlands & Wales Advanced Therapy Treatment Centre (MW-ATTC)

Open Date: 2018-03-01

Close Date: 2021-02-28

Articles (11)

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2024

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2022

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2022

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2022

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2022

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2022

Collaborators (9)

Felicity Evison

University Hospitals Birmingham NHS Foundation Trust

UNITED KINGDOM

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Robert Hoehndorf

SAUDI ARABIA

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Chris Sainsbury

Honorary Senior Clinical Lecturer

University of Glasgow

UNITED KINGDOM

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Elizabeth Sapey

University of Birmingham

UNITED KINGDOM

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Catherine Atkin

NIHR Academic Clinical Lecturer

University of Birmingham

UNITED KINGDOM

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Georgios Gkoutos

University of Birmingham

UNITED KINGDOM

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Luke Slater

University of Birmingham

UNITED KINGDOM

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Jackie Olley-Williams

University of Birmingham

UNITED KINGDOM

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Andreas Karwath

University of Birmingham

UNITED KINGDOM

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Simon Ball

Research Interests

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About

Recent Grants

Articles (11)

Adoption by clinicians of electronic order communications in NHS secondary care: a descriptive account

Does acute kidney injury alerting improve patient outcomes?

Benefits of electronic charts in intensive care and during a world health pandemic: advantages of the technology age.

Machine learning of COVID-19 clinical data identifies population structures with therapeutic potential.

Electronic prescribing systems as tools to improve patient care: a learning health systems approach to increase guideline concordant prescribing for venous thromboembolism prevention

The impact of changes in coding on mortality reports using the example of sepsis

Variability and performance of NHS England’s ‘reason to reside’ criteria in predicting hospital discharge in acute hospitals in England: a retrospective, observational cohort study

Effectiveness of clinical decision support in controlling inappropriate red blood cell and platelet transfusions, speciality specific responses and behavioural change.

Evaluating semantic similarity methods for comparison of text-derived phenotype profiles

Klarigi: Characteristic explanations for semantic biomedical data.

Evaluation of NEWS2 response thresholds in a retrospective observational study from a UK acute hospital

Collaborators (9)

Felicity Evison

Robert Hoehndorf

Chris Sainsbury

Elizabeth Sapey

Catherine Atkin

Georgios Gkoutos

Luke Slater

Jackie Olley-Williams

Andreas Karwath

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