Prediction of secondary testosterone deficiency using machine learning: A comparative analysis of ensemble and base classifiers, probability calibration, and sampling strategies in a slightly imbalanced dataset

Prediction of secondary testosterone deficiency using machine learning: A comparative analysis of ensemble and base classifiers, probability calibration, and sampling strategies in a slightly imbalanced dataset

Testosterone is the most important male sex hormone, and its deficiency brings many physical and mental harms. Efficiently identifying individuals with low testosterone is crucial prior to starting proper treatment. However, routine monitoring of testosterone levels can be costly in many regions, re...

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Bibliographic Details
Main Authors: Monique Tonani Novaes, Osmar Luiz Ferreira de Carvalho, Pedro Henrique Guimarães Ferreira, Taciana Leonel Nunes Tiraboschi, Caroline Santos Silva, Jean Carlos Zambrano, Cristiano Mendes Gomes, Eduardo de Paula Miranda, Osmar Abílio de Carvalho Júnior, José de Bessa Júnior
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Machine learning
Imbalanced data
Testosterone deficiency
Ensemble classifier
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914821000289

Internet

http://www.sciencedirect.com/science/article/pii/S2352914821000289

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