Papers: 10.1186/s12885-021-08647-1
https://doi.org/10.1186/s12885-021-08647-1
Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma
Cited by: 12
Author(s): Meng-Xiang Li, Xiaomeng Sun, Weigang Cheng, Han‐Li Ruan, Ke Liu, Ci Pan, Hai-Jun Xu, Shegan Gao, Xiaoshan Feng, Yi-Jun Qi
Published: almost 4 years ago
Software Mentions 5
Very Likely Science (85)
cran: e1071
Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU WienPapers that mentioned: 419
Very Likely Science (85)
cran: nnet
Feed-Forward Neural Networks and Multinomial Log-Linear ModelsPapers that mentioned: 296
Very Likely Science (93)
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Very Likely Science (90)