Cargando…
Investigating the Lung Adenocarcinoma Stem Cell Biomarker Expressions Using Machine Learning Approaches
The objective of the study is to look at the activation of stem cell-related markers in lung adenocarcinoma. Utilizing an unsupervised machine learning approach centered on the mRNA expression of pluripotent stem cells as well as its subsequent developed progeny, the mRNA stemness index of further a...
Autores principales: | Bhuvaneswari, M. S., Priyadharsini, S., Balaganesh, N., Theenathayalan, R., Hailu, Tegegne Ayalew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526580/ https://www.ncbi.nlm.nih.gov/pubmed/36193299 http://dx.doi.org/10.1155/2022/3518190 |
Ejemplares similares
-
mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers
por: Zhang, Yitong, et al.
Publicado: (2020) -
Investigation of the Temperature Compensation of Piezoelectric Weigh-In-Motion Sensors Using a Machine Learning Approach
por: Yang, Hailu, et al.
Publicado: (2022) -
Identification of a Sixteen-gene Prognostic Biomarker for Lung Adenocarcinoma Using a Machine Learning Method
por: Ma, Baoshan, et al.
Publicado: (2020) -
The CT delta-radiomics based machine learning approach in evaluating multiple primary lung adenocarcinoma
por: Ma, Yanqing, et al.
Publicado: (2022) -
Tissue-based Alzheimer gene expression markers–comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets
por: Scheubert, Lena, et al.
Publicado: (2012)