TY - GEN
T1 - A Survey on Cancer Molecular Subtype Classification using Deep learning
AU - Wahid, Mehwish
AU - Ahmed, Ghufran
AU - Hussain, Shahid
AU - Ansari, Asad Ahmed
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Deep learning(DL) is a sub-field of artificial intelligence that mimics the human brain through computation. It has proven its proficiency in different domains, including healthcare. It has shown promising results in various health-care applications, including cancer classification, prognosis, and molecular sub-typing of cancer. Molecular sub-typing provides biological insights regarding cancer heterogeneity that may lead to personalized medicines. The objective of this review is to discuss and compare the different deep learning models used for molecular subtyping along with the different types of omics data used like gene expression data, RNA sequence data, mRNA, and miRNA. We compared and summarized the different models and data types used for the cancer molecular subtyping in a tabular format.
AB - Deep learning(DL) is a sub-field of artificial intelligence that mimics the human brain through computation. It has proven its proficiency in different domains, including healthcare. It has shown promising results in various health-care applications, including cancer classification, prognosis, and molecular sub-typing of cancer. Molecular sub-typing provides biological insights regarding cancer heterogeneity that may lead to personalized medicines. The objective of this review is to discuss and compare the different deep learning models used for molecular subtyping along with the different types of omics data used like gene expression data, RNA sequence data, mRNA, and miRNA. We compared and summarized the different models and data types used for the cancer molecular subtyping in a tabular format.
UR - https://www.scopus.com/pages/publications/85159031281
UR - https://www.scopus.com/pages/publications/85159031281#tab=citedBy
U2 - 10.1109/iCoMET57998.2023.10099055
DO - 10.1109/iCoMET57998.2023.10099055
M3 - Conference contribution
AN - SCOPUS:85159031281
T3 - 2023 4th International Conference on Computing, Mathematics and Engineering Technologies: Sustainable Technologies for Socio-Economic Development, iCoMET 2023
BT - 2023 4th International Conference on Computing, Mathematics and Engineering Technologies
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2023
Y2 - 17 March 2023 through 18 March 2023
ER -
