Cargando…
Deep learning in systems medicine
Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, hetero...
Autores principales: | Wang, Haiying, Pujos-Guillot, Estelle, Comte, Blandine, de Miranda, Joao Luis, Spiwok, Vojtech, Chorbev, Ivan, Castiglione, Filippo, Tieri, Paolo, Watterson, Steven, McAllister, Roisin, de Melo Malaquias, Tiago, Zanin, Massimiliano, Rai, Taranjit Singh, Zheng, Huiru |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382976/ https://www.ncbi.nlm.nih.gov/pubmed/33197934 http://dx.doi.org/10.1093/bib/bbaa237 |
Ejemplares similares
-
Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data
por: Grissa, Dhouha, et al.
Publicado: (2016) -
Analytic Correlation Filtration: A New Tool to Reduce Analytical Complexity of Metabolomic Datasets
por: Monnerie, Stephanie, et al.
Publicado: (2019) -
Metabolomic and Lipidomic Signatures of Metabolic Syndrome and its Physiological Components in Adults: A Systematic Review
por: Monnerie, Stéphanie, et al.
Publicado: (2020) -
Global and Partial Effect Assessment in Metabolic Syndrome Explored by Metabolomics
por: Brandolini-Bunlon, Marion, et al.
Publicado: (2023) -
Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine
por: Zanin, Massimiliano, et al.
Publicado: (2017)