Publications

This selection of studies highlights the potential of real-world imaging data to advance AI applications in healthcare.

Featured Publication

Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging

npj Dig. Med. 2024 Jul;7(195). De Mortanges PA, et. Al.

Quantitative Evaluation of Large Language Models to Streamline Radiology Report Impressions: A Multimodal Retrospective Analysis

Radiology. 2024 Mar 310(3):e231593. Doshi R, et al.

Publications

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Federated Learning is not a Cure-all for Data Ethics

Nature Machine Intelligence. 2024 Mar 6(4). Bak M, et al.

How AI is being used to accelerate clinical trials

Nature. 2024 Mar 627:S2-S5. Hutson M.

Radiomic Predicts Early Response to CDK4/6 Inhibitors in Hormone Receptor Positive Metastatic Breast Cancer

npj Breast Cancer. 2023 Aug 9, 67. Khorrami, M. et al.

Real-World Evidence: A Primer

Pharmaceutical Medicine. 2023 Jan 37(1):25-36 Dang A.

Tumor Twistedness Serves as AI-Based Biomarker for Lung Cancer Immunotherapy

National Cancer Institute. 2023 Jan.

Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks

Radiol Artif Intell. 2022 Nov 2;4(6):e210284. Willemink MJ, et al.

Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks

Radiol Artif Intell. 2022 Nov 2;4(6):e210284. Willemink MJ, et al.

Data Preparation for Artificial Intelligence. Chapter In book: Artificial Intelligence in Cardiothoracic Imaging

Springer. 2022 Apr; Artificial Intelligence in Cardiothoracic Imaging (pp.37-43). ISBN 9783030920876. De Araujo AL, et al.

Data Preparation for Artificial Intelligence. Chapter In book: Artificial Intelligence in Cardiothoracic Imaging

Springer. 2022 Apr; Artificial Intelligence in Cardiothoracic Imaging (pp.37-43). ISBN 9783030920876. De Araujo AL, et al.

Generating Evidence for Artificial Intelligence-Based Medical Devices: A Framework for training, validation and evaluation

World Health Organization. 2021 Nov; Chapter 7. Internal Validation and Data Management (pp.33-35). ISBN: 9789240038462Digital Health and Innovation (DHI), Medical Devices and Diagnostics (MDD)

Generating Evidence for Artificial Intelligence-Based Medical Devices: A Framework for training, validation and evaluation

World Health Organization. 2021 Nov; Chapter 7. Internal Validation and Data Management (pp.33-35). ISBN: 9789240038462 Digital Health and Innovation (DHI), Medical Devices and Diagnostics (MDD)

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation

Invest Radiol. 2020 Sep;55(9):619-627. Wichmann JL, et al.

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation

Invest Radiol. 2020 Sep;55(9):619-627. Wichmann JL, et al.

Preparing Medical Imaging Data for Machine Learning

Radiology. 2020 Apr;295(1):4-15. Willemink MJ, et al.

Preparing Medical Imaging Data for Machine Learning

Radiology. 2020 Apr;295(1):4-15. Willemink MJ, et al.

Preparing Medical Imaging Data for Machine Learning

Radiology. 2020 Apr;295(1):4-15. Willemink MJ, et al.

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation

Invest Radiol. 2020 Sep;55(9):619-627. Wichmann JL, et al.

Data Preparation for Artificial Intelligence. Chapter In book: Artificial Intelligence in Cardiothoracic Imaging

Springer. 2022 Apr; Artificial Intelligence in Cardiothoracic Imaging (pp.37-43). ISBN 9783030920876. De Araujo AL, et al.

Generating Evidence for Artificial Intelligence-Based Medical Devices: A Framework for training, validation and evaluation

World Health Organization. 2021 Nov; Chapter 7. Internal Validation and Data Management (pp.33-35). ISBN: 9789240038462Digital Health and Innovation (DHI), Medical Devices and Diagnostics (MDD)

Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks

Radiol Artif Intell. 2022 Nov 2;4(6):e210284. Willemink MJ, et al.

Preparing Medical Imaging Data for Machine Learning

Radiology. 2020 Apr;295(1):4-15. Willemink MJ, et al.

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation

Invest Radiol. 2020 Sep;55(9):619-627. Wichmann JL, et al.

Data Preparation for Artificial Intelligence. Chapter In book: Artificial Intelligence in Cardiothoracic Imaging

Springer. 2022 Apr; Artificial Intelligence in Cardiothoracic Imaging (pp.37-43). ISBN 9783030920876. De Araujo AL, et al.

Generating Evidence for Artificial Intelligence-Based Medical Devices: A Framework for training, validation and evaluation

World Health Organization. 2021 Nov; Chapter 7. Internal Validation and Data Management (pp.33-35). ISBN: 9789240038462 Digital Health and Innovation (DHI), Medical Devices and Diagnostics (MDD)

Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks

Radiol Artif Intell. 2022 Nov 2;4(6):e210284. Willemink MJ, et al.

Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging

npj Dig. Med. 2024 Jul;7(195). De Mortanges PA, et. Al.

Radiomic Predicts Early Response to CDK4/6 Inhibitors in Hormone Receptor Positive Metastatic Breast Cancer

npj Breast Cancer. 2023 Aug 9, 67. Khorrami, M. et al.

Tumor Twistedness Serves as AI-Based Biomarker for Lung Cancer Immunotherapy

National Cancer Institute. 2023 Jan.

Real-World Evidence: A Primer

Pharmaceutical Medicine. 2023 Jan 37(1):25-36 Dang A.

How AI is being used to accelerate clinical trials

Nature. 2024 Mar 627:S2-S5. Hutson M.

Federated Learning is not a Cure-all for Data Ethics

Nature Machine Intelligence. 2024 Mar 6(4). Bak M, et al.

Quantitative Evaluation of Large Language Models to Streamline Radiology Report Impressions: A Multimodal Retrospective Analysis

Radiology. 2024 Mar 310(3):e231593. Doshi R, et al.

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