Cargando…
Artificial intelligence fusion for predicting survival of rectal cancer patients using immunohistochemical expression of Ras homolog family member B in biopsy
AIM: The process of biomarker discovery is being accelerated with the application of artificial intelligence (AI), including machine learning. Biomarkers of diseases are useful because they are indicators of pathogenesis or measures of responses to therapeutic treatments, and therefore, play a key r...
Autores principales: | Pham, Tuan D., Ravi, Vinayakumar, Luo, Bin, Fan, Chuanwen, Sun, Xiao-Feng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Open Exploration
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017185/ https://www.ncbi.nlm.nih.gov/pubmed/36937315 http://dx.doi.org/10.37349/etat.2023.00119 |
Ejemplares similares
-
Artificial intelligence–based 5‐year survival prediction and prognosis of DNp73 expression in rectal cancer patients
por: Pham, Tuan D., et al.
Publicado: (2020) -
Aplasia Ras Homologous Member I Gene and Development of Glial Tumors
por: Yakut, S, et al.
Publicado: (2011) -
Image-Based Network Analysis of DNp73 Expression by Immunohistochemistry in Rectal Cancer Patients
por: Pham, Tuan D., et al.
Publicado: (2020) -
Homology modeling in the time of collective and artificial intelligence
por: Hameduh, Tareq, et al.
Publicado: (2020) -
Artificial Intelligence in Medical Applications
por: Chan, Yung-Kuan, et al.
Publicado: (2018)