Cargando…
Pooling random forest and functional data analysis for biomedical signals supervised classification: Theory and application to electrocardiogram data
Scientific progress has contributed to creating many devices to gather vast amounts of biomedical data over time. The goal of these devices is generally to monitor people's health conditions, diagnose, and prevent patients' diseases, for example, to discover cardiovascular disorders or pre...
Autores principales: | Maturo, Fabrizio, Verde, Rosanna |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303904/ https://www.ncbi.nlm.nih.gov/pubmed/35184323 http://dx.doi.org/10.1002/sim.9353 |
Ejemplares similares
-
Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data
por: Viswanath, Satish, et al.
Publicado: (2012) -
Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling
por: Zhou, Fuqun, et al.
Publicado: (2016) -
Multiscale Supervised Classification of Point Clouds with Urban and Forest Applications
por: Cabo, Carlos, et al.
Publicado: (2019) -
Classification and Multivariate Analysis for Complex Data Structures
por: Fichet, Bernard, et al.
Publicado: (2011) -
Random forest for gene selection and microarray data classification
por: Moorthy, Kohbalan, et al.
Publicado: (2011)