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Publications

Image-based consensus molecular subtypes and colon cancer recurrence: Understanding the impact of lifestyle factors across subtypes of colon cancer

Wesselink E, Kok DE, Lafarge MW, van Lanen AS, Nagtegaal ID et al. (2026), Cancer Epidemiology, 103

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@article{imagebasedconse-2026/8,
  title={Image-based consensus molecular subtypes and colon cancer recurrence: Understanding the impact of lifestyle factors across subtypes of colon cancer},
  author={Wesselink E, Kok DE, Lafarge MW, van Lanen AS, Nagtegaal ID et al.},
  journal={Cancer Epidemiology},
  volume={103},
  year = "2026"
}

FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme

Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA (2026), Information Fusion, 130, 104080-104080

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@article{fedexitmissingc-2026/6,
  title={FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme},
  author={Saha P, Mishra D, Wagner F, Kamnitsas K & Noble JA},
  journal={Information Fusion},
  volume={130},
  pages={104080-104080},
  publisher={Elsevier},
  year = "2026"
}

SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images

Ockenden E, Anguajibi V, Mpooya S, Ntegeka B, Mugume T et al. (2026)

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@misc{schistotracknet-2026/6,
  title={SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images},
  author={Ockenden E, Anguajibi V, Mpooya S, Ntegeka B, Mugume T et al.},
  year = "2026"
}

SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video

Ockenden E, Anguajibi V, Mpooya S, Ntegeka B, Mugume T et al. (2026)

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@misc{schistotrackvid-2026/6,
  title={SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video},
  author={Ockenden E, Anguajibi V, Mpooya S, Ntegeka B, Mugume T et al.},
  year = "2026"
}

Accuracy of Diagnosis in Myeloproliferative Neoplasms With Splanchnic Vein Thrombosis (MPN‐SVT)

Sreedhar BR, Ryou H, O'Riordan A, Hargreaves R, Chauhan N et al. (2026), American Journal of Hematology

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@article{accuracyofdiagn-2026/5,
  title={Accuracy of Diagnosis in Myeloproliferative Neoplasms With Splanchnic Vein Thrombosis (MPN‐SVT)},
  author={Sreedhar BR, Ryou H, O'Riordan A, Hargreaves R, Chauhan N et al.},
  journal={American Journal of Hematology},
  year = "2026"
}

A Low-Cost, Microcontroller-Based Gas Delivery System for Respiratory Stimuli in MRI Studies

Blockley NP, Alzaidi AA, Milbourn CC, Bulte DP, Rudgewick-Brown A et al. (2026)

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@misc{alowcostmicroco-2026/5,
  title={A Low-Cost, Microcontroller-Based Gas Delivery System for Respiratory Stimuli in MRI Studies},
  author={Blockley NP, Alzaidi AA, Milbourn CC, Bulte DP, Rudgewick-Brown A et al.},
  year = "2026"
}

View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification

Yang Y, Yang Q, Peng C, Liu Y & Noble JA (2026), 00, 01-05

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@inproceedings{viewguidedmulti-2026/4,
  title={View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification},
  author={Yang Y, Yang Q, Peng C, Liu Y & Noble JA},
  booktitle={2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)},
  pages={01-05},
  year = "2026"
}

Patchsurg: Leveraging Synthetic Datasets for High-Fidelity Depth Estimation in Surgery

Xu Z, Zhang C, Rittscher J & Ali S (2026), 00, 1-5

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@inproceedings{patchsurglevera-2026/4,
  title={Patchsurg: Leveraging Synthetic Datasets for High-Fidelity Depth Estimation in Surgery},
  author={Xu Z, Zhang C, Rittscher J & Ali S},
  booktitle={2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)},
  pages={1-5},
  year = "2026"
}

Distilling Knowledge from Multiple Foundation Models for Accurate and Efficient Spatial Gene Expression Prediction

Li Z, Li B, Hu Y, Rittscher J & Verrill C (2026), 00, 1-4

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@inproceedings{distillingknowl-2026/4,
  title={Distilling Knowledge from Multiple Foundation Models for Accurate and Efficient Spatial Gene Expression Prediction},
  author={Li Z, Li B, Hu Y, Rittscher J & Verrill C},
  booktitle={2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)},
  pages={1-4},
  year = "2026"
}

Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priors.

Xu Z, Li B, Hu Y, Zhang C, East J et al. (2026), IEEE Trans Med Imaging, PP

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@article{selfsupervisedm-2026/3,
  title={Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priors.},
  author={Xu Z, Li B, Hu Y, Zhang C, East J et al.},
  journal={IEEE Trans Med Imaging},
  volume={PP},
  year = "2026"
}

118 (PB-118) Poster Combining MRI and Biological Risk in Premenopausal Women

Cox A, Bulte D & Brady M (2026), European Journal of Cancer, 237, 116386

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@inproceedings{pbpostercombini-2026/3,
  title={118 (PB-118) Poster Combining MRI and Biological Risk in Premenopausal Women},
  author={Cox A, Bulte D & Brady M},
  pages={116386},
  year = "2026"
}

Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography

Yang Y, Yang Q, Peng C, D'Alberti E, Patey O et al. (2026)

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@misc{orientationrobu-2026/2,
  title={Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography},
  author={Yang Y, Yang Q, Peng C, D'Alberti E, Patey O et al.},
  year = "2026"
}

Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referrals

Saha P, Alsharid M, Strong J & Noble JA (2026)

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@misc{experienceguide-2026/2,
  title={Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referrals},
  author={Saha P, Alsharid M, Strong J & Noble JA},
  year = "2026"
}

Picking the Right Specialist: Attentive Neural Process-based Selection of Task-Specialized Models as Tools for Agentic Healthcare Systems

Saha P, Strong J, Alsharid M, Mishra D & Noble JA (2026)

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@misc{pickingtheright-2026/2,
  title={Picking the Right Specialist: Attentive Neural Process-based Selection of Task-Specialized Models as Tools for Agentic Healthcare Systems},
  author={Saha P, Strong J, Alsharid M, Mishra D & Noble JA},
  year = "2026"
}

Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy

Valderrama NF, Morel L-O, Mweze DT, Derangère V, Desmoulins I et al. (2026), European Journal of Cancer, 234, 116222

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@article{chemopraidictbr-2026/2,
  title={Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy},
  author={Valderrama NF, Morel L-O, Mweze DT, Derangère V, Desmoulins I et al.},
  journal={European Journal of Cancer},
  volume={234},
  pages={116222},
  publisher={Elsevier},
  year = "2026"
}

Toward Integration of Molecular Measures and Artificial Intelligence-Based Assessments With Clinical End Points in Inflammatory Bowel Disease.

Reinisch W, Rittscher J, Iacucci M, Travis S & Friedrich M (2026), Gastroenterology

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@article{towardintegrati-2026/2,
  title={Toward Integration of Molecular Measures and Artificial Intelligence-Based Assessments With Clinical End Points in Inflammatory Bowel Disease.},
  author={Reinisch W, Rittscher J, Iacucci M, Travis S & Friedrich M},
  journal={Gastroenterology},
  year = "2026"
}

Latent Motion Profiling for Annotation-Free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos

Yang Y, Yang Q, Cui K, Peng C, D’Alberti E et al. (2026), Lecture Notes in Computer Science, 15973 LNCS, 316-325

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@inproceedings{latentmotionpro-2026/1,
  title={Latent Motion Profiling for Annotation-Free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos},
  author={Yang Y, Yang Q, Cui K, Peng C, D’Alberti E et al.},
  pages={316-325},
  year = "2026"
}

Self-supervised Normality Learning and Divergence Vector-Guided Model Merging for Zero-Shot Congenital Heart Disease Detection in Fetal Ultrasound Videos

Saha P, Mishra D, Hernandez-Cruz N, Patey O, Papageorghiou AT et al. (2026), Lecture Notes in Computer Science, 15966 LNCS, 560-571

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@inproceedings{selfsupervisedn-2026/1,
  title={Self-supervised Normality Learning and Divergence Vector-Guided Model Merging for Zero-Shot Congenital Heart Disease Detection in Fetal Ultrasound Videos},
  author={Saha P, Mishra D, Hernandez-Cruz N, Patey O, Papageorghiou AT et al.},
  pages={560-571},
  year = "2026"
}

A visually grounded language model for fetal ultrasound understanding.

Guo X, Alsharid M, Zhao H, Wang Y, Lander J et al. (2026), Nature biomedical engineering

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@article{avisuallyground-2026/1,
  title={A visually grounded language model for fetal ultrasound understanding.},
  author={Guo X, Alsharid M, Zhao H, Wang Y, Lander J et al.},
  journal={Nature biomedical engineering},
  year = "2026"
}

CtrlEndoDiff: Diffusion-Based Synthetic Image Generation for Enhanced ACF Segmentation

Albokhari R, Debnath B, Henry D, Johnson M, Bailey A et al. (2026), 319-329

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@misc{ctrlendodiffdif-2026/,
  title={CtrlEndoDiff: Diffusion-Based Synthetic Image Generation for Enhanced ACF Segmentation},
  author={Albokhari R, Debnath B, Henry D, Johnson M, Bailey A et al.},
  year = "2026"
}

Unsupervised Discovery of Spatiotypes and Context-Aware Graph Neural Networks for Modeling Clinical Endpoints

Dawood M, Thomas E, Cooper R, Pescia C, Sozanska A et al. (2026), 15970, 603-612

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@misc{unsuperviseddis-2026/,
  title={Unsupervised Discovery of Spatiotypes and Context-Aware Graph Neural Networks for Modeling Clinical Endpoints},
  author={Dawood M, Thomas E, Cooper R, Pescia C, Sozanska A et al.},
  year = "2026"
}

Learning to learn skill assessment for fetal ultrasound scanning

Wang Y, Yang Q, Drukker L, Papageorghiou AT, Hu Y et al. (2025)

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@misc{learningtolearn-2025/12,
  title={Learning to learn skill assessment for fetal ultrasound scanning},
  author={Wang Y, Yang Q, Drukker L, Papageorghiou AT, Hu Y et al.},
  year = "2025"
}

Redefining the topology of the human bone marrow using augmented spatial transcriptomic analysis

Cooper RA, Thomas E, Dawood M, Ryou H, Sozanska A et al. (2025)

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@misc{redefiningtheto-2025/12,
  title={Redefining the topology of the human bone marrow using augmented spatial transcriptomic analysis},
  author={Cooper RA, Thomas E, Dawood M, Ryou H, Sozanska A et al.},
  year = "2025"
}

The human factor in explainable artificial intelligence: clinician variability in trust, reliance, and performance.

Nicolson A, Bradburn E, Gal Y, Papageorghiou AT & Noble JA (2025), NPJ Digit Med, 8(1), 658

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@article{thehumanfactori-2025/11,
  title={The human factor in explainable artificial intelligence: clinician variability in trust, reliance, and performance.},
  author={Nicolson A, Bradburn E, Gal Y, Papageorghiou AT & Noble JA},
  journal={NPJ Digit Med},
  volume={8},
  pages={658},
  year = "2025"
}

On the public dissemination and open sourcing of ultrasound resources, datasets and deep learning models.

Alsharid M, Guo X, Men Q, Saha P, Mishra D et al. (2025), NPJ digital medicine

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@article{onthepublicdiss-2025/11,
  title={On the public dissemination and open sourcing of ultrasound resources, datasets and deep learning models.},
  author={Alsharid M, Guo X, Men Q, Saha P, Mishra D et al.},
  journal={NPJ digital medicine},
  year = "2025"
}

Toward precision pathology: Deep learning supported fibrosis grading augments performance of international hematopathologists in a large real-world cohort

Ebsworth T, Ruane S, Bhardwaj N, Cooper R, Green A et al. (2025), Blood, 146(Supplement 1), 4335-4335

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@article{towardprecision-2025/11,
  title={Toward precision pathology: Deep learning supported fibrosis grading augments performance of international hematopathologists in a large real-world cohort},
  author={Ebsworth T, Ruane S, Bhardwaj N, Cooper R, Green A et al.},
  journal={Blood},
  volume={146},
  pages={4335-4335},
  publisher={American Society of Hematology},
  year = "2025"
}

Histology-informed tiling of whole tissue sections improves the interpretability and predictability of cancer relapse and genetic alterations

Bonnaffé W, Hu Y, Chatrian A, Fan M, Malacrino S et al. (2025)

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@misc{histologyinform-2025/11,
  title={Histology-informed tiling of whole tissue sections improves the interpretability and predictability of cancer relapse and genetic alterations},
  author={Bonnaffé W, Hu Y, Chatrian A, Fan M, Malacrino S et al.},
  year = "2025"
}

SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation

Zhu J, Wu J, Ouyang C, Kamnitsas K & Noble JA (2025), 23731-23740

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@inproceedings{spaefficientuse-2025/10,
  title={SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation},
  author={Zhu J, Wu J, Ouyang C, Kamnitsas K & Noble JA},
  booktitle={2025 IEEE/CVF International Conference on Computer Vision (ICCV)},
  pages={23731-23740},
  year = "2025"
}

EXABS-184-MPN: Refining Diagnosis, Prognosis, and Management of MPNs With AI/ML

Cooper R, Thomas E, Hu X, Muhammad D, Ryou H et al. (2025), Clinical Lymphoma Myeloma & Leukemia, 25, s85-s86

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@article{exabsmpnrefinin-2025/9,
  title={EXABS-184-MPN: Refining Diagnosis, Prognosis, and Management of MPNs With AI/ML},
  author={Cooper R, Thomas E, Hu X, Muhammad D, Ryou H et al.},
  journal={Clinical Lymphoma Myeloma & Leukemia},
  volume={25},
  pages={s85-s86},
  year = "2025"
}

Decoding Fibrosis: Transcriptomic and Clinical Insights via AI-Derived Collagen Deposition Phenotypes in MASLD

Wojciechowska M, Thing M, Hu Y, Mazzoni G, Harder LM et al. (2025)

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@inproceedings{decodingfibrosi-2025/9,
  title={Decoding Fibrosis: Transcriptomic and Clinical Insights via AI-Derived Collagen Deposition Phenotypes in MASLD},
  author={Wojciechowska M, Thing M, Hu Y, Mazzoni G, Harder LM et al.},
  year = "2025"
}