Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data-Reference-Cited by-同舟云学术

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Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data

Published:2020-09-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
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Author:

Zare Fatima¹,Noorbakhsh Javad²,Wang Tianyu¹,Chuang Jeffrey H.³,Nabavi Sheida¹

Affiliation:

1. Computer Science and Engineering Department, University of Connecticut, Storrs, Connecticut

2. The Jackson Laboratory For Genomic Medicine, Farmington, Connecticut

3. The Jackson Laboratory For Genomic Medicine, UConn Health, Department of Genetics and Genome Sciences, Farmington, Connecticut

Funder

National Cancer Institute

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3388440.3412414

Reference36 articles.

1. Classification of breast cancer histology images using Convolutional Neural Networks

2. Computer aided diagnostic tools aim to empower rather than replace pathologists: Lessons learned from computational chess

3. Immune and Stromal Classification of Colorectal Cancer Is Associated with Molecular Subtypes and Relevant for Precision Immunotherapy

4. Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival

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1. A review of fusion methods for omics and imaging data;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2022

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