Lauren Oakden‐Rayner

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

2024 · 1.422 Zit. · BMJ

AI recognition of patient race in medical imaging: a modelling study

2022 · 465 Zit. · The Lancet Digital Health

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

2023 · 235 Zit. · Nature Medicine

The medical algorithmic audit

2022 · 199 Zit. · The Lancet Digital Health

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods

2025 · 175 Zit. · BMJ

Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study

2022 · 84 Zit. · The Lancet Digital Health

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

Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA

2024 · 71 Zit. · Insights into Imaging

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA

2024 · 47 Zit. · Radiology Artificial Intelligence

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA

2024 · 41 Zit. · Canadian Association of Radiologists Journal

Medical artificial intelligence for clinicians: the lost cognitive perspective

2024 · 36 Zit. · The Lancet Digital Health

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

2024 · 32 Zit. · Nature Communications

Developing, purchasing, implementing and monitoring AI tools in radiology: Practical considerations. A multi‐society statement from the ACR, CAR, ESR, RANZCR & RSNA

2024 · 29 Zit. · Journal of Medical Imaging and Radiation Oncology

What's fair is… fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning

2023 · 26 Zit.