James Thomas

Professor of Social Research and Policy

University College London

United Kingdom

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James Thomas is a Professor of Social Research and Policy at University College London, UK. His research interests encompass the use of large language models in data extraction for toxicology, public involvement in health theory development, and the health implications of e-cigarettes. He has also focused on machine learning applications in systematic reviews and the evaluation of health interventions, contributing to advancements in health equity and automated information extraction.

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2020

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2020

Collaborators (15)

Bridget Candy

University College London

UNITED KINGDOM

James Thomas

Research Interests

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About

Articles (24)

ContReviews: A content-based recommendation system for updating Living Evidences in health care

Large language models for data extraction in toxicology: implications and lessons learned from the clinical evidence domain

Public Involvement in Complex Theorising: A Co‐Produced Logic Model of the Role of Context in Shaping Child Health

Harmful health effects of e-cigarettes (vapes) and other non-tobacco oral nicotine products, trends in their use, and interventions: living protocol for a living evidence map and linked research digests

Data extraction methods for systematic review (semi)automation: Update of a living systematic review

Automated information extraction for behavioural interventions: evaluation and reflections on interdisciplinary AI development

Methods used to conceptualize dimensions of health equity impacts of public health interventions in systematic reviews

Cost-effectiveness of Microsoft Academic Graph with machine learning for automated study identification in a living map of coronavirus disease 2019 (COVID-19) research

Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project

The FAIR database: facilitating access to public health research literature

Predicting outcomes of smoking cessation interventions in novel scenarios using ontology-informed, interpretable machine learning

Critical elements of synthesis questions are incompletely reported: survey of systematic reviews of intervention effects

Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project

Data extraction methods for systematic review (semi)automation: Update of a living systematic review

Accuracy and Efficiency of Machine Learning–Assisted Risk-of-Bias Assessments in “Real-World” Systematic Reviews

Influences on User Trust in Healthcare Artificial Intelligence: A Systematic Review

Cost-effectiveness of Microsoft Academic Graph with machine learning for automated study identification in a living map of coronavirus disease 2019 (COVID-19) research

Data extraction methods for systematic review (semi)automation: A living systematic review

The use of ‘PICO for synthesis’ and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions

Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology

Current practice in systematic reviews including the ‘PICO for each synthesis’ and methods other than meta-analysis: protocol for a cross-sectional study

Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology

The Human Behaviour-Change Project: An artificial intelligence system to answer questions about changing behaviour

Data extraction methods for systematic review (semi)automation: A living review protocol

Collaborators (15)

Bridget Candy

Janna Hastings

Emma Norris

Iain Marshall

Babatunde Olorisade

Alison Wright

Gareth Hollands

Alison O'Mara-Eves

ZHIXUE ZHAO

Thomas Hartung

Ian Shemilt

Rafael Peñaloza

Marie Johnston

Joanne McKenzie

Sandy Oliver

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