- B. Bejnordi, …, M. Shaban, N. Rajpoot, …, “Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women with Breast Cancer” JAMA. 2017;318(22):2199–2210. doi:10.1001/jama.2017.14585 (Impact Factor: 44.405).
- N. Alsubaie, M. Shaban, D. Snead, A. Khurram, N. Rajpoot, "A Multi-Resolution Deep Learning Framework for Lung Adenocarcinoma Growth Pattern Classification", 22nd Annual Conference, MIUA 2018, Southhampton, UK, July 09–11, 2018, Proceedings
- R. Awan, N. A. Koohbanani, M Shaban, A. Lisowska, N. Rajpoot, “Context-Aware Learning Using Transferable Features for Classification of Breast Cancer Histology Images”, Campilho A., Karray F., ter Haar Romeny B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science, vol 10882. Springer, Cham.
- S. Graham, M. Shaban, T. Qaiser, S. A. Khurram, N. Rajpoot, “Classification of lung cancer histology images using patch-level summary statistics”, SPIE Digital Pathology 2018.
- M. Shaban, A. Mahmood, S. Ali, and N. Rajpoot, “Multi-person Head Segmentation in Low Resolution Crowd Scenes Using Convolutional Encoder-Decoder Framework”, Workshop on Representation, analysis and recognition of shape and motion from image data (RFMI 2017).
A. Agarwalla, M. Shaban, N. Rajpoot, “Representation-Aggregation Networks for Segmentation of Multi-Gigapixel Histology Images”, BMVC Workshop on Deep Learning on Irregular Domains (DLID 2017).
- M. Shaban, Syed Ali Khurram, Mariam Hassan, Sajid Mushtaq, Asif Loya, Nasir Rajpoot, “Prognostic significance of automated score of tumor infiltrating lymphocytes in oral cancer”, J Clin Oncol 36, 2018, suppl; abstr e18036 (Impact Factor: 24.008).