2019
DOI: 10.1186/s12885-019-6338-1
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Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients

Abstract: BackgroundDeciphering the meaning of the human DNA is an outstanding goal which would revolutionize medicine and our way for treating diseases. In recent years, non-coding RNAs have attracted much attention and shown to be functional in part. Yet the importance of these RNAs especially for higher biological functions remains under investigation.MethodsIn this paper, we analyze RNA-seq data, including non-coding and protein coding RNAs, from lung adenocarcinoma patients, a histologic subtype of non-small-cell l… Show more

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Cited by 18 publications
(17 citation statements)
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“…Recent results for deep learning networks and support vector machines demonstrate that feature selection can negatively affect the prediction performance for high-dimensional genomic data ( Smolander et al, 2019 ). However, whether these results translate to data in other domains remains to be seen.…”
Section: Robustness Issues Of ML and Ai Modelsmentioning
confidence: 99%
“…Recent results for deep learning networks and support vector machines demonstrate that feature selection can negatively affect the prediction performance for high-dimensional genomic data ( Smolander et al, 2019 ). However, whether these results translate to data in other domains remains to be seen.…”
Section: Robustness Issues Of ML and Ai Modelsmentioning
confidence: 99%
“…For instance, a deep learning method set the record for the classification of handwritten digits of the MNIST data set with an error rate of 0.21% (Wan et al, 2013 ). Further application areas include image recognition (Krizhevsky et al, 2012a ; LeCun et al, 2015 ), speech recognition (Graves et al, 2013 ), natural language understanding (Sarikaya et al, 2014 ), acoustic modeling (Mohamed et al, 2011 ) and computational biology (Leung et al, 2014 ; Alipanahi et al, 2015 ; Zhang S. et al, 2015 ; Smolander et al, 2019a , b ).…”
Section: Introductionmentioning
confidence: 99%
“…Since LUAD is the most frequent lung cancer type, many works have been published for LUAD and control classification. Smolander et al presented a deep learning model using gene expression from coding RNA, and non-coding RNA [ 25 ]. They obtained a classification accuracy of 95.97% using coding RNA.…”
Section: Related Workmentioning
confidence: 99%