most citedhist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images

63 citations · 107 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV202363 cited

hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images

Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham +3

Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemist…

eess.IV20235 cited

Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans

Jiayi Zhu, Bart Bolsterlee, Brian V. Y. Chow +2

Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information acquired from a single dimensionality…

cs.LG202338 cited

Fully Elman Neural Network: A Novel Deep Recurrent Neural Network Optimized by an Improved Harris Hawks Algorithm for Classification of Pulmonary Arterial Wedge Pressure

Masoud Fetanat, Michael Stevens, Pankaj Jain +3

Heart failure (HF) is one of the most prevalent life-threatening cardiovascular diseases in which 6.5 million people are suffering in the USA and more than 23 million worldwide. Me…

eess.IV20211 cited

Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation

Tariq M. Khan, Syed S. Naqvi, Erik Meijering

Recent progress in encoder-decoder neural network architecture design has led to significant performance improvements in a wide range of medical image segmentation tasks. However,…