Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder
摘要 與前列腺癌和乳腺癌等常見癌症不同，罕見癌症的腫瘤分級很困難，而且很大程度上是不確定的，因爲樣本量小，承擔這樣的任務需要大量的時間和經驗，而且提取人類觀察到的模式本身就很困難。最具挑戰性的例子之一是肝內膽管癌(ICC)，這是一種起源於膽道系統的原發性肝癌，其腫瘤異質性是公認的，並且沒有分級範例或預後生物標誌物。本文提出了一種新的基於無監督深卷積自動編碼器的聚類模型，該模型基於視覺相似性將246
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相關文章
- 1. Deep Unsupervised Clustering Using Mixture of Autoencoders(2017)
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- 4. Deep Temporal Clustering: Fully unsupervised learning of time-domain features
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