Bilal A. Mateen

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

2024 · 1.422 Zit. · BMJ

Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness

2020 · 460 Zit. · BMJ

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

2022 · 427 Zit. · Nature Medicine

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

2022 · 294 Zit. · BMJ

Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol

2021 · 282 Zit. · BMJ Open

The value of standards for health datasets in artificial intelligence-based applications

2023 · 235 Zit. · Nature Medicine

A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI

2021 · 217 Zit. · Nature Medicine

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

2024 · 84 Zit. · The Lancet Digital Health

Tackling bias in AI health datasets through the STANDING Together initiative

2022 · 77 Zit. · Nature Medicine

Improving the quality of machine learning in health applications and clinical research

2020 · 65 Zit. · Nature Machine Intelligence

The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence

2025 · 41 Zit. · Nature Medicine

Machine learning and AI research for Patient Benefit: 20 Critical\n Questions on Transparency, Replicability, Ethics and Effectiveness

2018 · 17 Zit. · arXiv (Cornell University)

Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness

2018 · 17 Zit. · University of Birmingham Research Portal (University of Birmingham)

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

2024 · 12 Zit. · NEJM AI

Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review

2024 · 10 Zit. · Clinical Imaging