Martijn P. A. Starmans

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

2025 · 270 Zit. · BMJ

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

2023 · 74 Zit. · European Radiology Experimental

Radiology AI Deployment and Assessment Rubric (RADAR) to bring value-based AI into radiological practice

2024 · 25 Zit. · Insights into Imaging

AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines

2025 · 13 Zit. · EBioMedicine

ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment—practice recommendations by the European Society of Medical Imaging Informatics

2024 · 5 Zit. · European Radiology

Auditing Unfair Biases in CNN-Based Diagnosis of Alzheimer’s Disease

2023 · 4 Zit. · Lecture notes in computer science

New implementation of data standards for AI in oncology. Experience from the EuCanImage project

2024 · 3 Zit. · medRxiv

New implementation of data standards for AI in oncology: Experience from the EuCanImage project

2024 · 3 Zit. · GigaScience

A Review of Methods for Trustworthy AI in Medical Imaging: The FUTURE-AI Guidelines

2025 · 3 Zit. · IEEE Journal of Biomedical and Health Informatics

AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines

2024 · 1 Zit. · White Rose Research Online (University of Leeds, The University of Sheffield, University of York)

Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages

2025 · 1 Zit. · ArXiv.org

Bias and Fairness in Radiomics: A Comparative Analysis of Machine Learning Models on Four Oncology Datasets

2026 · 0 Zit. · International Journal of Imaging Systems and Technology