A nine-gene signature identification and prognostic risk prediction for patients with lung adenocarcinoma using novel machine learning approach.
Eskezeia Yihunie DessieJan-Gowth ChangYa-Sian ChangPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- kaplan meier
- machine learning
- survival analysis
- prognostic models
- survival data
- risk factors
- high risk
- escherichia coli
- clinical data
- prediction accuracy
- signature recognition
- lung disease
- lung cancer
- intensive care
- gene expression
- breast cancer
- predictive modeling
- statistical methods
- regression model
- information extraction
- ct images
- prediction model
- risk management
- machine learning algorithms
- gene prediction
- prostate cancer
- chronic disease
- splice site
- radiation doses
- prediction error
- signature verification
- risk assessment
- microarray
- statistical analysis
- text mining
- natural language processing
- decision trees
- feature selection
- learning algorithm
- data mining
- neural network
- gene expression data
- machine learning methods
- breast cancer patients
- body mass index