Cargando…
Using a Decision Tree Algorithm Predictive Model for Sperm Count Assessment and Risk Factors in Health Screening Population
PURPOSE: 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 ab...
Autores principales: | Huang, Hung-Hsiang, Lu, Chi-Jie, Jhou, Mao-Jhen, Liu, Tzu-Chi, Yang, Chih-Te, Hsieh, Shang-Ju, Yang, Wen-Jen, Chang, Hsiao-Chun, Chen, Ming-Shu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10658962/ https://www.ncbi.nlm.nih.gov/pubmed/38024496 http://dx.doi.org/10.2147/RMHP.S433193 |
Ejemplares similares
-
Machine Learning Predictive Models for Evaluating Risk Factors Affecting Sperm Count: Predictions Based on Health Screening Indicators
por: Huang, Hung-Hsiang, et al.
Publicado: (2023) -
Utilization of Decision Tree Algorithms for Supporting the Prediction of Intensive Care Unit Admission of Myasthenia Gravis: A Machine Learning-Based Approach
por: Chang, Che-Cheng, et al.
Publicado: (2022) -
Integrating Health Data-Driven Machine Learning Algorithms to Evaluate Risk Factors of Early Stage Hypertension at Different Levels of HDL and LDL Cholesterol
por: Liao, Pen-Chih, et al.
Publicado: (2022) -
Integrated Machine Learning Decision Tree Model for Risk Evaluation in Patients with Non-Valvular Atrial Fibrillation When Taking Different Doses of Dabigatran
por: Huang, Yung-Chuan, et al.
Publicado: (2023) -
A Hybrid Risk Factor Evaluation Scheme for Metabolic Syndrome and Stage 3 Chronic Kidney Disease Based on Multiple Machine Learning Techniques
por: Jhou, Mao-Jhen, et al.
Publicado: (2022)