TY - JOUR
T1 - Deep learning in the biomedical applications
T2 - Recent and future status
AU - Zemouri, Ryad
AU - Zerhouni, Noureddine
AU - Racoceanu, Daniel
N1 - Publisher Copyright:
© 2019 by the authors.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Deep neural networks represent, nowadays, the most effective machine learning technology in biomedical domain. In this domain, the different areas of interest concern the Omics (study of the genome-genomics-and proteins-transcriptomics, proteomics, and metabolomics), bioimaging (study of biological cell and tissue), medical imaging (study of the human organs by creating visual representations), BBMI (study of the brain and body machine interface) and public and medical health management (PmHM). This paper reviews the major deep learning concepts pertinent to such biomedical applications. Concise overviews are provided for the Omics and the BBMI.We end our analysis with a critical discussion, interpretation and relevant open challenges.
AB - Deep neural networks represent, nowadays, the most effective machine learning technology in biomedical domain. In this domain, the different areas of interest concern the Omics (study of the genome-genomics-and proteins-transcriptomics, proteomics, and metabolomics), bioimaging (study of biological cell and tissue), medical imaging (study of the human organs by creating visual representations), BBMI (study of the brain and body machine interface) and public and medical health management (PmHM). This paper reviews the major deep learning concepts pertinent to such biomedical applications. Concise overviews are provided for the Omics and the BBMI.We end our analysis with a critical discussion, interpretation and relevant open challenges.
KW - Biomedical applications
KW - Brain and body machine interface
KW - Deep neural networks
KW - Medical imaging
KW - Omics
UR - http://www.scopus.com/inward/record.url?scp=85067125293&partnerID=8YFLogxK
U2 - 10.3390/app9081526
DO - 10.3390/app9081526
M3 - Article
AN - SCOPUS:85067125293
SN - 2076-3417
VL - 9
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 8
M1 - 1526
ER -