Context-Aware Learning Using Transferable Features for Classification of Breast Cancer Histology Images

Citation:

Ruqayya Awan, Navid Alemi Koohbanani, Muhammad Shaban, Anna Lisowska, and Nasir Rajpoot. 2018. “Context-Aware Learning Using Transferable Features for Classification of Breast Cancer Histology Images.” In International Conference Image Analysis and Recognition, Pp. 788–795. Springer, Cham.

Recent Publications

Deep Learning based Digital Cell Profiles for Risk Stratification of Urine Cytology Images

Ruqayya Awan, Ksenija Benes, Ayesha Azam, Tzu-Hsi Song, Muhammad Shaban, Clare Verrill, Yee Wah Tsang, David Snead, Fayyaz Minhas, and Nasir Rajpoot. 2021. “Deep Learning based Digital Cell Profiles for Risk Stratification of Urine Cytology Images.” Cytometry Part A.Read more

Pan-cancer integrative histology-genomic analysis via interpretable multimodal deep learning

Richard J Chen, Ming Y Lu, Drew FK Williamson, Tiffany Y Chen, Jana Lipkova, Muhammad Shaban, Maha Shady, Mane Williams, Bumjin Joo, Zahra Noor, and others. 2021. “Pan-cancer integrative histology-genomic analysis via interpretable multimodal deep learning.” arXiv preprint arXiv:2108.02278.Read more

Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction Using Patch-Based Graph Convolutional Networks

Richard J Chen, Ming Y Lu, Muhammad Shaban, Chengkuan Chen, Tiffany Y Chen, Drew FK Williamson, and Faisal Mahmood. 2021. “Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction Using Patch-Based Graph Convolutional Networks.” In International Conference on Medical Image Computing and Computer-Assisted Intervention, Pp. 339–349. Springer.Read more

A digital score of tumour-associated stroma infiltrating lymphocytes predicts survival in head and neck squamous cell carcinoma

Muhammad Shaban, Shan Ahmed e Raza, Mariam Hassan, Arif Jamshed, Sajid Mushtaq, Asif Loya, Nikolaos Batis, Jill Brooks, Paul Nankivell, Neil Sharma, and others. 2021. “A digital score of tumour-associated stroma infiltrating lymphocytes predicts survival in head and neck squamous cell carcinoma.” https://arxiv.org/abs/2104.12862.Read more

Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview

Hanya Mahmood, Muhammad Shaban, Nasir Rajpoot, and Syed A Khurram. 2021. “Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview.” British Journal of Cancer, Pp. 1–7.Read more

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