Cargando…
A Dynamic Model for Imputing Missing Medical Data: A Multiobjective Particle Swarm Optimization Algorithm
Missing data occurs in all research, especially in medical studies. Missing data is the situation in which a part of research data has not been reported. This will result in the incompatibility of the sample and the population and misguided conclusions. Missing data is usual in research, and the ext...
Autores principales: | Almasinejad, Peyman, Golabpour, Amin, Mollakhalili Meybodi, Mohammad Reza, Mirzaie, Kamal, Khosravi, Ahmad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519720/ https://www.ncbi.nlm.nih.gov/pubmed/34659677 http://dx.doi.org/10.1155/2021/1203726 |
Ejemplares similares
-
Corrigendum to “A Dynamic Model for Imputing Missing Medical Data: A Multiobjective Particle Swarm Optimization Algorithm”
por: Almasinejad, Peyman, et al.
Publicado: (2022) -
Dynamic Shannon Performance in a Multiobjective Particle Swarm Optimization
por: Pires, E. J. Solteiro, et al.
Publicado: (2019) -
Providing an imputation algorithm for missing values of longitudinal data using Cuckoo search algorithm: A case study on cervical dystonia
por: Golabpour, Amin, et al.
Publicado: (2017) -
Multilevel Multiobjective Particle Swarm Optimization Guided Superpixel Algorithm for Histopathology Image Detection and Segmentation
por: Kanadath, Anusree, et al.
Publicado: (2023) -
Multiswarm comprehensive learning particle swarm optimization for solving multiobjective optimization problems
por: Yu, Xiang, et al.
Publicado: (2017)