Cargando…
Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches
Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low–middle-income cou...
Autores principales: | Sajid, Mirza Rizwan, Almehmadi, Bader A., Sami, Waqas, Alzahrani, Mansour K., Muhammad, Noryanti, Chesneau, Christophe, Hanif, Asif, Khan, Arshad Ali, Shahbaz, Ahmad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657087/ https://www.ncbi.nlm.nih.gov/pubmed/34886312 http://dx.doi.org/10.3390/ijerph182312586 |
Ejemplares similares
-
Exploration of Black Boxes of Supervised Machine Learning Models: A Demonstration on Development of Predictive Heart Risk Score
por: Sajid, Mirza Rizwan, et al.
Publicado: (2022) -
Simple Instrumental and Visual Tests for Nonlaboratory Environmental Control
por: Eksperiandova, L. P., et al.
Publicado: (2016) -
Modifiable risk factors and overall cardiovascular mortality: Moderation of urbanization
por: Sajid, Mirza Rizwan, et al.
Publicado: (2020) -
Nonlaboratory-Based Risk Assessment Algorithm for Undiagnosed Type 2 Diabetes Developed on a Nation-Wide Diabetes Survey
por: Zhou, Xianghai, et al.
Publicado: (2013) -
Estimation of 10‐year cardiovascular risk among adult population in western Nepal using nonlaboratory‐based WHO/ISH chart, 2023: A cross‐sectional study
por: Sitaula, Deekshanta, et al.
Publicado: (2023)