Cargando…
Machine Learning and Deep Learning for the Pharmacogenomics of Antidepressant Treatments
A growing body of evidence now proposes that machine learning and deep learning techniques can serve as a vital foundation for the pharmacogenomics of antidepressant treatments in patients with major depressive disorder (MDD). In this review, we focus on the latest developments for pharmacogenomics...
Autores principales: | Lin, Eugene, Lin, Chieh-Hsin, Lane, Hsien-Yuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean College of Neuropsychopharmacology
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553527/ https://www.ncbi.nlm.nih.gov/pubmed/34690113 http://dx.doi.org/10.9758/cpn.2021.19.4.577 |
Ejemplares similares
-
Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches
por: Lin, Eugene, et al.
Publicado: (2020) -
Deep Learning with Neuroimaging and Genomics in Alzheimer’s Disease
por: Lin, Eugene, et al.
Publicado: (2021) -
Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer’s Disease
por: Chang, Chun-Hung, et al.
Publicado: (2021) -
Applying a bagging ensemble machine learning approach to predict functional outcome of schizophrenia with clinical symptoms and cognitive functions
por: Lin, Eugene, et al.
Publicado: (2021) -
Prediction of functional outcomes of schizophrenia with genetic biomarkers using a bagging ensemble machine learning method with feature selection
por: Lin, Eugene, et al.
Publicado: (2021)