By Associate Professor Ewan Kerr Alexander Millar

Preprints

Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, MM-SurvNet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion, , http://dx.doi.org/10.48550/arxiv.2402.11788

Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion, , http://dx.doi.org/10.48550/arxiv.2402.10717

Rahaman MM; Millar EKA; Meijering E, 2023, Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning, , http://dx.doi.org/10.21203/rs.3.rs-2983276/v1

Mondol RK; Millar EKA; Graham PH; Browne L; Sowmya A; Meijering E, 2023, hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images, , http://dx.doi.org/10.48550/arxiv.2304.04507

Rahaman MM; Millar EKA; Meijering E, 2023, Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learning, , http://dx.doi.org/10.1038/s41598-023-40219-0

Teo WS; Holliday H; Karthikeyan N; Cazet AS; Roden DL; Harvey K; Konrad CV; Murali R; Varghese BA; P. T. A; Chan C-L; McFarland A; Junankar S; Ye S; Yang J; Nikolic I; Shah JS; Baker LA; Millar EKA; Naylor MJ; Ormandy CJ; Lakhani SR; Kaplan W; Mellick AS; O’Toole SA; Swarbrick A; Nair R, 2018, Id proteins promote a cancer stem cell phenotype in triple negative breast cancer via negative regulation of Robo1, , http://dx.doi.org/10.1101/497313

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