Prediction of successful aging using ensemble machine learning algorithms
Abstract Background Aging is a chief risk factor for most chronic illnesses and infirmities. The growth in the aged population increases medical costs, thus imposing a heavy financial burden on families and communities. Successful aging (SA) is a positive and qualitative view of aging. From a biomed...
Main Authors: | Zahra Asghari Varzaneh, Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2022-10-01
|
Series: | BMC Medical Informatics and Decision Making |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12911-022-02001-6 |
Similar Items
-
Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms?
by: Razieh Mirzaeian, et al.
Published: (2023-08-01) -
Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms
by: Azita Yazdani, et al.
Published: (2023-10-01) -
Comparing machine learning algorithms for predicting COVID-19 mortality
by: Khadijeh Moulaei, et al.
Published: (2022-01-01) -
Predictive modeling for COVID-19 readmission risk using machine learning algorithms
by: Mostafa Shanbehzadeh, et al.
Published: (2022-05-01) -
Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia
by: Mostafa Shanbehzadeh, et al.
Published: (2022-09-01)