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Mahmood Lab @ Harvard/MGB's Projects

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Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

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A vision-language foundation model for computational pathology - Nature Medicine

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Demographic bias in misdiagnosis by computational pathology models - Nature Medicine

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Deep learning enabled assessment of cardiac allograft rejection from endomyocardial biopsies- Nature Medicine

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HEST: Bringing Spatial Transcriptomics and Histopathology together

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Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)

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Federated Learning for Computational Pathology - Medical Image Analysis

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Multimodal AI for Renal Allograft Biopsy Assessment

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Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications

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MArker imputation model for multiple\underlineX IMages

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Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images - ICCV 2021

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Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images - CVPR 2023

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Multimodal prototyping for cancer survival prediction - ICML 2024

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Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024

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Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks - MICCAI 2021

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Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell

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Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering

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Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024

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Transcriptomics-guided Slide Representation Learning in Computational Pathology - CVPR 2024

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AI-based pathology predicts origins for cancers of unknown primary - Nature

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Analysis of 3D pathology samples using weakly supervised AI - Cell

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Towards a general-purpose foundation model for computational pathology - Nature Medicine

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Variance pooling to incorporate ITH in CPath models - MICCAI 2022

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