Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms?

Mirzaeian, Razieh; Nopour, Raoof; Asghari Varzaneh, Zahra; Shafiee, Mohsen; Shanbehzadeh, Mostafa; Kazemi-Arpanahi, Hadi

Mirzaeian, Razieh; Nopour, Raoof; Asghari Varzaneh, Zahra; Shafiee, Mohsen; Shanbehzadeh, Mostafa; Kazemi-Arpanahi, Hadi.

Affiliation

Mirzaeian R; Department of Health Information Management, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Nopour R; Student Research Committee, School of Health Management and Information Sciences Branch, Iran University of Medical Sciences, Tehran, Iran.
Asghari Varzaneh Z; Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.
Shafiee M; Department of Nursing, Abadan University of Medical Sciences, Abadan, Iran.
Shanbehzadeh M; Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
Kazemi-Arpanahi H; Department of Health Information Technology, Abadan University of Medical Sciences, Abadan, Iran. h.kazemi@abadanums.ac.ir.

Biomed Eng Online ; 22(1): 85, 2023 Aug 29.

Article in En | MEDLINE | ID: mdl-37644599

Subject(s)
Key words

Aged; Data mining; Health-related quality of life; Machine learning; Quality of life; Successful aging

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Random Forest Type of study: Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adult / Aged / Humans Language: En Journal: Biomed Eng Online Journal subject: ENGENHARIA BIOMEDICA Year: 2023 Document type: Article Affiliation country: Irán Country of publication: Reino Unido

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