Chris McWilliams

Chris McWilliams

University of Bristol

H-index: 8

Europe-United Kingdom

About Chris McWilliams

Chris McWilliams, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at University of Bristol, specializes in the field of Data science. Intensive care. Community and conservation ecology. Complexity..

His recent articles reflect a diverse array of research interests and contributions to the field:

Explainable hierarchical clustering for patient subtyping and risk prediction

CATS: Cloud-native time-series data annotation tool for intensive care

Identification, Explanation and Clinical Evaluation of Hospital Patient Subtypes

Capturing requirements for a data annotation tool for intensive care: Experimental user-centered design study

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study

Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

Strategies for engaging clinical participants in the co-design of software for healthcare domains

Conventional and Bayesian workflows for clinical prediction modelling of severe Covid-19 outcomes based on clinical biomarker test results: LabMarCS: Laboratory Markers of …

Chris McWilliams Information

University

Position

Senior Research Associate

Citations(all)

511

Citations(since 2020)

445

Cited By

182

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Chris McWilliams Skills & Research Interests

Data science. Intensive care. Community and conservation ecology. Complexity.

Top articles of Chris McWilliams

Explainable hierarchical clustering for patient subtyping and risk prediction

Experimental Biology and Medicine

2023/12/15

CATS: Cloud-native time-series data annotation tool for intensive care

SoftwareX

2023/12/1

Chris Mcwilliams
Chris Mcwilliams

H-Index: 5

Identification, Explanation and Clinical Evaluation of Hospital Patient Subtypes

2023/2/13

Capturing requirements for a data annotation tool for intensive care: Experimental user-centered design study

arXiv preprint arXiv:2309.16500

2023/9/28

Chris Mcwilliams
Chris Mcwilliams

H-Index: 5

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study

JMIR Human Factors

2023/9/26

Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

arXiv preprint arXiv:2309.04211

2023/9/8

Strategies for engaging clinical participants in the co-design of software for healthcare domains

arXiv preprint arXiv:2308.16631

2023/4/31

Chris Mcwilliams
Chris Mcwilliams

H-Index: 5

Conventional and Bayesian workflows for clinical prediction modelling of severe Covid-19 outcomes based on clinical biomarker test results: LabMarCS: Laboratory Markers of …

2022/9/17

Bayesian Prediction of Severe Outcomes in the LabMarCS: Laboratory Markers of COVID-19 Severity-Bristol Cohort

medRxiv

2022/9/17

Supporting patient nutrition in critical care units

2022/6/10

Elias Pimenidis
Elias Pimenidis

H-Index: 10

Chris Mcwilliams
Chris Mcwilliams

H-Index: 5

Requirements for a bespoke intensive care unit dashboard in response to the COVID-19 pandemic: semistructured interview study

JMIR human factors

2022/4/13

Requirements for bespoke ICU Dashboard in response to the COVID-19 Pandemic

JMIR Human Factors

2022/1/3

The dynamics of procalcitonin in COVID-19 patients admitted to Intensive care unit-a multi-centre cohort study in the South West of England, UK.

Journal of Infection

2021/6/1

The value of triage during periods of intense COVID-19 demand: Simulation modeling study

Medical Decision Making

2021/5

Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool

medRxiv

2021/7/16

Chris Mcwilliams
Chris Mcwilliams

H-Index: 5

Avon Huxor
Avon Huxor

H-Index: 20

COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care

Health care management science

2020/9

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