2023
DOI: 10.2147/rmhp.s433193
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Using a Decision Tree Algorithm Predictive Model for Sperm Count Assessment and Risk Factors in Health Screening Population

Hung-Hsiang Huang,
Chi-Jie Lu,
Mao-Jhen Jhou
et al.

Abstract: Approximately 20% of couples face infertility challenges and struggle to conceive naturally. Despite advances in artificial reproduction, its success hinges on sperm quality. Our previous study used five machine learning (ML) algorithms, random forest, stochastic gradient boosting, least absolute shrinkage and selection operator regression, ridge regression, and extreme gradient boosting, to model health data from 1375 Taiwanese males and identified ten risk factors affecting sperm count. Methods: We employed … Show more

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Cited by 2 publications
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“…5,6 The latest technologies, such as artificial intelligence (AI), have improved healthcare delivery significantly in different settings. 7,8 Even though AI technology can be traced back to the mid-20th century, recent decades have witnessed significant growth in its usage in healthcare. 9,10 AI in the healthcare sector decreases the workload of healthcare workers, makes a quicker diagnosis, and leads to efficient patient care, including care for mental health.…”
Section: Introductionmentioning
confidence: 99%
“…5,6 The latest technologies, such as artificial intelligence (AI), have improved healthcare delivery significantly in different settings. 7,8 Even though AI technology can be traced back to the mid-20th century, recent decades have witnessed significant growth in its usage in healthcare. 9,10 AI in the healthcare sector decreases the workload of healthcare workers, makes a quicker diagnosis, and leads to efficient patient care, including care for mental health.…”
Section: Introductionmentioning
confidence: 99%