Tom Pollard

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

2024 · 84 Zit. · The Lancet Digital Health

A “datathon” model to support cross-disciplinary collaboration

2016 · 77 Zit. · Science Translational Medicine

Bridging the Health Data Divide

2016 · 54 Zit. · Journal of Medical Internet Research

The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data

2019 · 47 Zit. · PLoS ONE

INSPIRE, a publicly available research dataset for perioperative medicine

2024 · 36 Zit. · Scientific Data

Big data and machine learning in critical care: Opportunities for collaborative research

2018 · 35 Zit. · Medicina Intensiva

Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

2014 · 29 Zit. · DSpace@MIT (Massachusetts Institute of Technology)

“Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets

2020 · 18 Zit. · npj Digital Medicine

Turning the crank for machine learning: ease, at what expense?

2019 · 17 Zit. · The Lancet Digital Health

Enabling Machine Learning in Critical Care.

2017 · 13 Zit. · PubMed

Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations

2024 · 12 Zit. · NEJM AI

Artificial intelligence in the clinical setting

2022 · 7 Zit. · European Journal of Anaesthesiology

Raising awareness of potential biases in medical machine learning: Experience from a Datathon

2024 · 3 Zit.

Health Data Nexus: an open data platform for AI research and education in medicine

2025 · 1 Zit. · GigaScience

FHIR-AgentBench: Benchmarking LLM Agents for Realistic Interoperable EHR Question Answering

2025 · 1 Zit. · ArXiv.org