CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training

Background: The state-of-the-art deep learning based cancer type prediction can only predict cancer types whose samples are available during the training where the sample size is commonly large. In this paper, we consider how to utilize the existing training samples to predict cancer types unseen du...

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Bibliographic Details
Main Authors:	Chen, Y. (Author), Chiu, Y.-C (Author), Huang, Y. (Author), Mostavi, M. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	1-nearest neighbor Accuracy Improvement Cancer gene markers Cancer type prediction Convolutional neural networks Deep learning Diagnosis Diseases Forecasting Gene expression Gene expression profiles genetics Genomics human Humans Learning systems Metastatic cancers Metastatic tumors neoplasm Neoplasms Neural Networks, Computer One-shot learning Primary and metastatic tumors Related functions Similarity functions transcriptome Transcriptome Transfer learning Tumors
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CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training

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