@String(PAMI = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV = {Int. J. Comput. Vis.})
@String(CVPR= {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV= {Int. Conf. Comput. Vis.})
@String(ECCV= {Eur. Conf. Comput. Vis.})
@String(NIPS= {Adv. Neural Inform. Process. Syst.})
@String(ICPR = {Int. Conf. Pattern Recog.})
@String(BMVC= {Brit. Mach. Vis. Conf.})
@String(TOG= {ACM Trans. Graph.})
@String(TIP  = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TMM  = {IEEE Trans. Multimedia})
@String(ACMMM= {ACM Int. Conf. Multimedia})
@String(ICME = {Int. Conf. Multimedia and Expo})
@String(ICASSP=	{ICASSP})
@String(ICIP = {IEEE Int. Conf. Image Process.})
@String(ACCV  = {ACCV})
@String(ICLR = {Int. Conf. Learn. Represent.})
@String(IJCAI = {IJCAI})
@String(PR   = {Pattern Recognition})
@String(AAAI = {AAAI})
@String(CVPRW= {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(CSVT = {IEEE Trans. Circuit Syst. Video Technol.})

@String(SPL	= {IEEE Sign. Process. Letters})
@String(VR   = {Vis. Res.})
@String(JOV	 = {J. Vis.})
@String(TVC  = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
@String(CGF  = {Comput. Graph. Forum})
@String(CVM = {Computational Visual Media})


@String(PAMI  = {IEEE TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(NIPS  = {NeurIPS})
@String(ICPR  = {ICPR})
@String(BMVC  =	{BMVC})
@String(TOG   = {ACM TOG})
@String(TIP   = {IEEE TIP})
@String(TVCG  = {IEEE TVCG})
@String(TCSVT = {IEEE TCSVT})
@String(TMM   =	{IEEE TMM})
@String(ACMMM = {ACM MM})
@String(ICME  =	{ICME})
@String(ICASSP=	{ICASSP})
@String(ICIP  = {ICIP})
@String(ACCV  = {ACCV})
@String(ICLR  = {ICLR})
@String(IJCAI = {IJCAI})
@String(PR = {PR})
@String(AAAI = {AAAI})
@String(CVPRW= {CVPRW})
@String(CSVT = {IEEE TCSVT})



@article{5299287,
  author={Gurcan, Metin N. and Boucheron, Laura E. and Can, Ali and Madabhushi, Anant and Rajpoot, Nasir M. and Yener, Bulent},
  journal={IEEE Reviews in Biomedical Engineering}, 
  title={Histopathological Image Analysis: A Review}, 
  year={2009},
  volume={2},
  number={},
  pages={147-171}
}

@article{shao2021transmil,
  title={Transmil: Transformer based correlated multiple instance learning for whole slide image classification},
  author={Shao, Zhuchen and Bian, Hao and Chen, Yang and Wang, Yifeng and Zhang, Jian and Ji, Xiangyang and others},
  journal={Advances in neural information processing systems},
  volume={34},
  pages={2136--2147},
  year={2021}
}

@inproceedings{li2024dynamic,
  title={Dynamic graph representation with knowledge-aware attention for histopathology whole slide image analysis},
  author={Li, Jiawen and Chen, Yuxuan and Chu, Hongbo and Sun, Qiehe and Guan, Tian and Han, Anjia and He, Yonghong},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={11323--11332},
  year={2024}
}

@article{zheng2022graph,
  title={A graph-transformer for whole slide image classification},
  author={Zheng, Yi and Gindra, Rushin H and Green, Emily J and Burks, Eric J and Betke, Margrit and Beane, Jennifer E and Kolachalama, Vijaya B},
  journal={IEEE transactions on medical imaging},
  volume={41},
  number={11},
  pages={3003--3015},
  year={2022},
  publisher={IEEE}
}

@article{hanna2019implementation,
  title={Implementation of digital pathology offers clinical and operational increase in efficiency and cost savings},
  author={Hanna, Matthew G and Reuter, Victor E and Samboy, Jennifer and England, Christine and Corsale, Lorraine and Fine, Samson W and Agaram, Narasimhan P and Stamelos, Evangelos and Yagi, Yukako and Hameed, Meera and others},
  journal={Archives of pathology \& laboratory medicine},
  volume={143},
  number={12},
  pages={1545--1555},
  year={2019},
  publisher={the College of American Pathologists}
}

@article{kumar2020whole,
  title={Whole slide imaging (WSI) in pathology: current perspectives and future directions},
  author={Kumar, Neeta and Gupta, Ruchika and Gupta, Sanjay},
  journal={Journal of digital imaging},
  volume={33},
  number={4},
  pages={1034--1040},
  year={2020},
  publisher={Springer}
}

@article{tizhoosh2018artificial,
  title={Artificial intelligence and digital pathology: challenges and opportunities},
  author={Tizhoosh, Hamid Reza and Pantanowitz, Liron},
  journal={Journal of pathology informatics},
  volume={9},
  number={1},
  pages={38},
  year={2018},
  publisher={Elsevier}
}

@article{afonso2024multiple,
  title={Multiple Instance Learning for WSI: A comparative analysis of attention-based approaches},
  author={Afonso, Martim and Bhawsar, Praphulla MS and Saha, Monjoy and Almeida, Jonas S and Oliveira, Arlindo L},
  journal={Journal of Pathology Informatics},
  volume={15},
  pages={100403},
  year={2024},
  publisher={Elsevier}
}

@article{yilmaz2024advancing,
  title={Advancing Artificial Intelligence Integration Into the Pathology Workflow: Exploring Opportunities in Gastrointestinal Tract Biopsies},
  author={Yilmaz, Fazilet and Brickman, Arlen and Najdawi, Fedaa and Yakirevich, Evgeny and Egger, Robert and Resnick, Murray B},
  journal={Laboratory Investigation},
  volume={104},
  number={5},
  pages={102043},
  year={2024},
  publisher={Elsevier}
}

@article{lu2021data,
  title={Data-efficient and weakly supervised computational pathology on whole-slide images},
  author={Lu, Ming Y and Williamson, Drew FK and Chen, Tiffany Y and Chen, Richard J and Barbieri, Matteo and Mahmood, Faisal},
  journal={Nature biomedical engineering},
  volume={5},
  number={6},
  pages={555--570},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@article{brody2021attentive,
  title={How attentive are graph attention networks?},
  author={Brody, Shaked and Alon, Uri and Yahav, Eran},
  journal={arXiv preprint arXiv:2105.14491},
  year={2021}
}

@inproceedings{cai2021graphnorm,
  title={Graphnorm: A principled approach to accelerating graph neural network training},
  author={Cai, Tianle and Luo, Shengjie and Xu, Keyulu and He, Di and Liu, Tie-yan and Wang, Liwei},
  booktitle={International Conference on Machine Learning},
  pages={1204--1215},
  year={2021},
  organization={PMLR}
}

@inproceedings{yang2024mambamil,
  title={Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathology},
  author={Yang, Shu and Wang, Yihui and Chen, Hao},
  booktitle={International conference on medical image computing and computer-assisted intervention},
  pages={296--306},
  year={2024},
  organization={Springer}
}

@inproceedings{li2021dual,
  title={Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning},
  author={Li, Bin and Li, Yin and Eliceiri, Kevin W},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={14318--14328},
  year={2021}
}

%%% ACMIL
@inproceedings{zhang2024attention,
  title={Attention-challenging multiple instance learning for whole slide image classification},
  author={Zhang, Yunlong and Li, Honglin and Sun, Yunxuan and Zheng, Sunyi and Zhu, Chenglu and Yang, Lin},
  booktitle={European conference on computer vision},
  pages={125--143},
  year={2024},
  organization={Springer}
}


%%% DTFT-MIL
@inproceedings{zhang2022dtfd,
  title={Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification},
  author={Zhang, Hongrun and Meng, Yanda and Zhao, Yitian and Qiao, Yihong and Yang, Xiaoyun and Coupland, Sarah E and Zheng, Yalin},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={18802--18812},
  year={2022}
}

%%% MHIM-MIL
@inproceedings{tang2023multiple,
  title={Multiple instance learning framework with masked hard instance mining for whole slide image classification},
  author={Tang, Wenhao and Huang, Sheng and Zhang, Xiaoxian and Zhou, Fengtao and Zhang, Yi and Liu, Bo},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={4078--4087},
  year={2023}
}

@article{tang2026multiple,
  title={Multiple Instance Learning Framework with Masked Hard Instance Mining for Gigapixel Histopathology Image Analysis},
  author={Tang, Wenhao and Huang, Sheng and Fang, Heng and Zhou, Fengtao and Liu, Bo and Liu, Qingshan},
  journal={International Journal of Computer Vision},
  volume={134},
  number={1},
  pages={41},
  year={2026},
  publisher={Springer}
}

%%% This is the review article for GNN in histopathology
@article{brussee2025graph,
  title={Graph neural networks in histopathology: Emerging trends and future directions},
  author={Brussee, Siemen and Buzzanca, Giorgio and Schrader, Anne MR and Kers, Jesper},
  journal={Medical Image Analysis},
  pages={103444},
  year={2025},
  publisher={Elsevier}
}


@inproceedings{ilse2018attention,
  title={Attention-based deep multiple instance learning},
  author={Ilse, Maximilian and Tomczak, Jakub and Welling, Max},
  booktitle={International conference on machine learning},
  pages={2127--2136},
  year={2018},
  organization={PMLR}
}

@inproceedings{chan2023histopathology,
  title={Histopathology whole slide image analysis with heterogeneous graph representation learning},
  author={Chan, Tsai Hor and Cendra, Fernando Julio and Ma, Lan and Yin, Guosheng and Yu, Lequan},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={15661--15670},
  year={2023}
}

@inproceedings{hou2022h,
  title={H\^{} 2-MIL: exploring hierarchical representation with heterogeneous multiple instance learning for whole slide image analysis},
  author={Hou, Wentai and Yu, Lequan and Lin, Chengxuan and Huang, Helong and Yu, Rongshan and Qin, Jing and Wang, Liansheng},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={36},
  number={1},
  pages={933--941},
  year={2022}
}

@INPROCEEDINGS{5206848,
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Kai Li and Li Fei-Fei},
  booktitle={2009 IEEE Conference on Computer Vision and Pattern Recognition}, 
  title={ImageNet: A large-scale hierarchical image database}, 
  year={2009},
  volume={},
  number={},
  pages={248-255},
  keywords={Large-scale systems;Image databases;Explosions;Internet;Robustness;Information retrieval;Image retrieval;Multimedia databases;Ontologies;Spine},
  doi={10.1109/CVPR.2009.5206848}}

%%%% This is pretrained feature extractor, UNI from Mahmood's Lab
@article{chen2024towards,
  title={Towards a general-purpose foundation model for computational pathology},
  author={Chen, Richard J and Ding, Tong and Lu, Ming Y and Williamson, Drew FK and Jaume, Guillaume and Song, Andrew H and Chen, Bowen and Zhang, Andrew and Shao, Daniel and Shaban, Muhammad and others},
  journal={Nature medicine},
  volume={30},
  number={3},
  pages={850--862},
  year={2024},
  publisher={Nature Publishing Group US New York}
}

@article{tomczak2015review,
  title={Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge},
  author={Tomczak, Katarzyna and Czerwi{\'n}ska, Patrycja and Wiznerowicz, Maciej},
  journal={Contemporary Oncology/Wsp{\'o}{\l}czesna Onkologia},
  year={2015},
  number={1},
  pages={68--77},
  publisher={Termedia}
}

@inproceedings{liu2025hasd,
  title={Hasd: hierarchical adaption for pathology slide-level domain-shift},
  author={Liu, Jingsong and Li, Han and Yang, Chen and Deutges, Michael and Sadafi, Ario and You, Xin and Breininger, Katharina and Navab, Nassir and Sch{\"u}ffler, Peter J},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={332--342},
  year={2025},
  organization={Springer}
}

@inproceedings{pocevivciute2024detecting,
  title={Detecting domain shift in multiple instance learning for digital pathology using fr{\'e}chet domain distance},
  author={PoceviVCiute, M and Eilertsen, G and Garvin, S and Lundstrom, C},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={157--167},
  year={2024}
}

%%%%%%%%%% Patch-GCN %%%%%%%%%%
@inproceedings{chen2021whole,
  title={Whole slide images are 2d point clouds: Context-aware survival prediction using patch-based graph convolutional networks},
  author={Chen, Richard J and Lu, Ming Y and Shaban, Muhammad and Chen, Chengkuan and Chen, Tiffany Y and Williamson, Drew FK and Mahmood, Faisal},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={339--349},
  year={2021},
  organization={Springer}
}

@article{campanella2019clinical,
  title={Clinical-grade computational pathology using weakly supervised deep learning on whole slide images},
  author={Campanella, Gabriele and Hanna, Matthew G and Geneslaw, Luke and Miraflor, Allen and Werneck Krauss Silva, Vitor and Busam, Klaus J and Brogi, Edi and Reuter, Victor E and Klimstra, David S and Fuchs, Thomas J},
  journal={Nature medicine},
  volume={25},
  number={8},
  pages={1301--1309},
  year={2019},
  publisher={Nature Publishing Group US New York}
}

@inproceedings{chen2020simple,
  title={Simple and deep graph convolutional networks},
  author={Chen, Ming and Wei, Zhewei and Huang, Zengfeng and Ding, Bolin and Li, Yaliang},
  booktitle={International conference on machine learning},
  pages={1725--1735},
  year={2020},
  organization={PMLR}
}

%%% BRACS Dataset
@article{brancati2022bracs,
  title={Bracs: A dataset for breast carcinoma subtyping in h\&e histology images},
  author={Brancati, Nadia and Anniciello, Anna Maria and Pati, Pushpak and Riccio, Daniel and Scognamiglio, Giosu{\`e} and Jaume, Guillaume and De Pietro, Giuseppe and Di Bonito, Maurizio and Foncubierta, Antonio and Botti, Gerardo and others},
  journal={Database},
  volume={2022},
  pages={baac093},
  year={2022},
  publisher={Oxford University Press UK}
}

@inproceedings{chattopadhay2018grad,
  title={Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks},
  author={Chattopadhay, Aditya and Sarkar, Anirban and Howlader, Prantik and Balasubramanian, Vineeth N},
  booktitle={2018 IEEE winter conference on applications of computer vision (WACV)},
  pages={839--847},
  year={2018},
  organization={IEEE}
}

@article{zhang2025patches,
  title={From patches to WSIs: A systematic review of deep Multiple Instance Learning in computational pathology},
  author={Zhang, Yuchen and Gao, Zeyu and He, Kai and Li, Chen and Mao, Rui},
  journal={Information Fusion},
  volume={119},
  pages={103027},
  year={2025},
  publisher={Elsevier}
}