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Learning disentangled representations in the imaging domain

Medical image analysis, 2022-08, Vol.80, p.102516-102516, Article 102516

2022

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Causal machine learning for healthcare and precision medicine

Royal Society open science, 2022-08, Vol.9 (8), p.220638

2022

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Compositionally Equivariant Representation Learning

IEEE transactions on medical imaging, 2024-06, Vol.43 (6), p.2169-2179

2024

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The role of noise in denoising models for anomaly detection in medical images

Medical image analysis, 2023-12, Vol.90, p.102963-102963, Article 102963

2023

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Acute stroke CDS: automatic retrieval of thrombolysis contraindications from unstructured clinical letters

Frontiers in digital health, 2023-06, Vol.5, p.1186516-1186516

2023

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Assessing Machine Learning for Diagnostic Classification of Hypertension Types Identified by Ambulatory Blood Pressure Monitoring

CJC open (Online), 2024-06, Vol.6 (6), p.798-804

2024

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Templated Text Synthesis for Expert-Guided Multi-Label Extraction from Radiology Reports

Machine learning and knowledge extraction, 2021-06, Vol.3 (2), p.299-317, Article 299

2021

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Survey: Leakage and Privacy at Inference Time

IEEE transactions on pattern analysis and machine intelligence, 2023-07, Vol.45 (7), p.9090-9108

2023

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Evaluating the Impact on Clinical Task Efficiency of a Natural Language Processing Algorithm for Searching Medical Documents: Prospective Crossover Study

JMIR medical informatics, 2022-10, Vol.10 (10), p.e39616-e39616

2022

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MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images

IEEE transactions on medical imaging, 2022-10, Vol.41 (10), p.2728-2738

2022

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Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022, p.1-5

2022

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Segmentation of White Matter Hyperintensities and Ischaemic Stroke Lesions in Structural MRI

Medical Image Understanding and Analysis, p.3-17

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Anomaly Detection via Context and Local Feature Matching

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022, p.1-5

2022

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Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports

Frontiers in digital health, 2023-09, Vol.5, p.1184919-1184919

2023

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Attaining Human-Level Performance with Atlas Location Autocontext for Anatomical Landmark Detection in 3D CT Data

Computer Vision – ECCV 2018 Workshops, p.470-484

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Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting

Machine Learning in Medical Imaging, 2023, Vol.14348, p.413-423

2023

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What is Healthy? Generative Counterfactual Diffusion for Lesion Localization

Deep Generative Models, p.34-44

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Group Distributionally Robust Knowledge Distillation

Machine Learning in Medical Imaging, 2023, Vol.14349, p.234-242

2023

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Clinically Focussed Evaluation of Anomaly Detection and Localisation Methods Using Inpatient CT Head Data

Data Augmentation, Labelling, and Imperfections, 2024, p.63-72

2024

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Compositional Representation Learning for Brain Tumour Segmentation

Domain Adaptation and Representation Transfer, 2023, Vol.14293, p.41-51

2023

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HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information

Medical Applications with Disentanglements, p.15-21

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Improving Image Representations via MoCo Pre-training for Multimodal CXR Classification

Medical Image Understanding and Analysis, p.623-635

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vMFNet: Compositionality Meets Domain-Generalised Segmentation

Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, p.704-714

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Crowdsourcing Labels for Pathological Patterns in CT Lung Scans: Can Non-experts Contribute Expert-Quality Ground Truth?

Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, p.96-105

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Paying Per-Label Attention for Multi-label Extraction from Radiology Reports

Interpretable and Annotation-Efficient Learning for Medical Image Computing, p.277-289

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Learning disentangled representations in the imaging domain

Causal machine learning for healthcare and precision medicine

Compositionally Equivariant Representation Learning

The role of noise in denoising models for anomaly detection in medical images

Acute stroke CDS: automatic retrieval of thrombolysis contraindications from unstructured clinical letters

Assessing Machine Learning for Diagnostic Classification of Hypertension Types Identified by Ambulatory Blood Pressure Monitoring

Templated Text Synthesis for Expert-Guided Multi-Label Extraction from Radiology Reports

Survey: Leakage and Privacy at Inference Time

Evaluating the Impact on Clinical Task Efficiency of a Natural Language Processing Algorithm for Searching Medical Documents: Prospective Crossover Study

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images

Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers

Segmentation of White Matter Hyperintensities and Ischaemic Stroke Lesions in Structural MRI

Anomaly Detection via Context and Local Feature Matching

Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports

Attaining Human-Level Performance with Atlas Location Autocontext for Anatomical Landmark Detection in 3D CT Data

Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting

What is Healthy? Generative Counterfactual Diffusion for Lesion Localization

Group Distributionally Robust Knowledge Distillation

Clinically Focussed Evaluation of Anomaly Detection and Localisation Methods Using Inpatient CT Head Data

Compositional Representation Learning for Brain Tumour Segmentation

HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information

Improving Image Representations via MoCo Pre-training for Multimodal CXR Classification

vMFNet: Compositionality Meets Domain-Generalised Segmentation

Crowdsourcing Labels for Pathological Patterns in CT Lung Scans: Can Non-experts Contribute Expert-Quality Ground Truth?

Paying Per-Label Attention for Multi-label Extraction from Radiology Reports

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