Structured crowdsourcing enables convolutional segmentation of histology images. - Mohamed Amgad; Habiba Elfandy; Hagar Hussein; Lamees A. Atteya; Mai A. T. Elsebaie; Lamia S. Abo Elnasr; Rokia Adel Sakr; Hazem S. E. Salem; Ahmed F. Ismail; Anas M. Saad; Joumana Ahmed; Maha A. T. Elsebaie; et al. (Bioinform., 2019)

HistomicsML2.0: Fast interactive machine learning for whole slide imaging data. - Sanghoon Lee 007; Mohamed Amgad; Deepak Roy Chittajallu; Matt McCormick 001; Brian P. Pollack; Habiba Elfandy; Hagar Hussein; David A. Gutman; Lee A. D. Cooper (CoRR, 2020)

NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation. - Mohamed Amgad; Lamees A. Atteya; Hagar Hussein; Kareem Hosny Mohammed; Ehab Hafiz; Maha A. T. Elsebaie; Ahmed M. Alhusseiny; Mohamed Atef AlMoslemany; Abdelmagid M. Elmatboly; Philip A. Pappalardo; Rokia Adel Sakr; Pooya Mobadersany; et al. (CoRR, 2021)

Explainable nucleus classification using Decision Tree Approximation of Learned Embeddings. - Mohamed Amgad; Lamees A. Atteya; Hagar Hussein; Kareem Hosny Mohammed; Ehab Hafiz; Maha A. T. Elsebaie; Pooya Mobadersany; David Manthey; David A. Gutman; Habiba Elfandy; Lee A. D. Cooper (Bioinform., 2022)