Classification of miRNA expression data using random forests for cancer diagnosis
Cancer is a major leading cause of death and responsible for around 13% of all deaths world-wide. Cancer incidence rate is growing at an alarming rate in Malaysia and the world as we know it. It is estimated that statistically one out of every four Malaysians will develop cancer by the age of 75. Co...
Main Authors: | Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
IEEE
2016
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/54510/ http://irep.iium.edu.my/54510/ http://irep.iium.edu.my/54510/ http://irep.iium.edu.my/54510/7/54510.pdf http://irep.iium.edu.my/54510/8/54510-Classification%20of%20miRNA%20Expression%20Data%20Using%20Random%20Forests%20for%20Cancer%20Diagnosis_SCOPUS.pdf |
Similar Items
-
Evaluation of miRNA-based classifiers for cancer diagnosis
by: Razak, Eliza, et al.
Published: (2017) -
Evaluation of miRNA-based classifiers for cancer diagnosis
by: Razak, Eliza, et al.
Published: (2017) -
Cancer histopathologic subtypes prediction from miRNA expression data using pattern recognition
by: Razak, Eliza, et al.
Published: (2018) -
Ectopic miRNA network and the crosstalk between different signalling pathways during EMT and MET
by: Razak, Eliza, et al.
Published: (2016) -
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
by: Zarzar, Mouayad, et al.
Published: (2015)