Publications

(2023). DrML: Diagnosing and Rectifying Vision Models using Language. ICLR.

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(2023). Self-supervised learning for medical image classification: a systematic review and implementation guidelines. IEEE Transactions on Medical Imaging.

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(2023). Self-supervised learning for medical image classification: a systematic review and implementation guidelines. Nature Digital Medicine (Under Review).

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(2022). Adapting pre-trained vision transformers from 2D to 3D through weight inflation improves medical image segmentation. ML4H.

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(2022). Developing medical imaging AI for emerging infectious diseases. Nature Communications.

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(2022). AI recognition of patient race in medical imaging: a modelling study. The Lancet Digital Health.

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(2022). Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. Nature Digital Medicine.

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(2022). Development and validation of a prognostic AI biomarker using multi-modal deep learning with digital histopathology in localized prostate cancer on NRG Oncology phase III clinical trials.. Journal of Clinical Oncology.

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(2021). Automatic lung nodule segmentation and intra-nodular heterogeneity image generation. IEEE Journal of Biomedical and Health Informatics.

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(2021). RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR. arXiv.

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(2021). GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-Efficient Medical Image Recognition. ICCV.

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(2020). Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection. Nature Scientific Reports.

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(2020). Biomedical Graph Visualizer for Identifying Drug Candidates. biorXiv.

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(2020). Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines. Nature Digital Medicine.

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(2020). PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. Nature Digital Medicine.

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(2020). OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations. arXiv.

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(2019). Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks. PLOS Computational Biology.

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