Philippe Lambin

Machine Learning methods for Quantitative Radiomic Biomarkers

2015 · 1.008 Zit. · Scientific Reports

Transparency of deep neural networks for medical image analysis: A review of interpretability methods

2021 · 462 Zit. · Computers in Biology and Medicine

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer

2015 · 406 Zit. · Frontiers in Oncology

Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework

2020 · 259 Zit. · Methods

Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods

2021 · 186 Zit. · Journal of Personalized Medicine

Deep learning in fracture detection: a narrative review

2020 · 163 Zit. · Acta Orthopaedica

Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care

2020 · 133 Zit. · JCO Clinical Cancer Informatics

Blockchain for Privacy Preserving and Trustworthy Distributed Machine Learning in Multicentric Medical Imaging (C-DistriM)

2020 · 86 Zit. · IEEE Access

CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools

2022 · 39 Zit. · Frontiers in Oncology

Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness

2024 · 38 Zit. · Computational and Structural Biotechnology Journal

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

2023 · 38 Zit. · arXiv (Cornell University)

Artificial intelligence in oncology

2020 · 23 Zit. · Artificial Intelligence in Medicine

Privacy preserving distributed learning classifiers – Sequential learning with small sets of data

2021 · 23 Zit. · Computers in Biology and Medicine

Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure

2025 · 21 Zit. · Insights into Imaging

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

2021 · 12 Zit. · arXiv (Cornell University)