By Associate Professor Ewan Kerr Alexander Millar

Preprints

Rahaman MM; Millar EKA; Meijering E, 2025, Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images, http://arxiv.org/abs/2503.10731v1

Alexandrou S; Lee CS; Fernandez KJ; Wiharja CE; Eshraghi L; Reeves J; Reed DA; Portman N; Phan Z; Milioli HH; Nikolic I; Cadell AL; Croucher DR; Simpson KJ; Lim E; Hickey TE; Millar EKA; Alves CL; Ditzel HJ; Caldon CE, 2025, JNK pathway suppression drives resistance to combination endocrine therapy and CDK4/6 inhibition in ER+ breast cancer, http://dx.doi.org/10.1101/2025.01.08.631992

Mondol RK; Millar EKA; Graham PH; Browne L; Sowmya A; Meijering E, 2025, GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology, http://arxiv.org/abs/2501.04206v1

Sandarenu P; Chen J; Slapetova I; Browne L; Graham PH; Swarbrick A; Millar EKA; Song Y; Meijering E, 2024, Semi-supervised variational autoencoder for cell feature extraction in multiplexed immunofluorescence images, http://arxiv.org/abs/2406.15727v2

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://arxiv.org/abs/2402.11788v1

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/10.1109/JBHI.2024.3418341

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/10.3390/cancers15092569

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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