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Current Updates on Involvement of Artificial Intelligence and Machine Learning in Semen Analysis
Manesh Kumar Panner Selvam1, Ajaya Kumar Moharana1,2, Saradha Baskaran1
1Department of Urology, Tulane University School of Medicine, New Orleans, LA 70112, USA.
Medicina (Kaunas, Lithuania)
|February 24, 2024
Summary
Artificial intelligence (AI) enhances semen analysis accuracy for male infertility diagnosis. AI algorithms show promise in improving sperm examination and selection by specialists.
Area of Science:
- Reproductive Medicine
- Biomedical Engineering
- Artificial Intelligence
Background:
- Rising infertility rates necessitate improved diagnostic tools.
- Current semen analysis methods lack consistent accuracy.
- Artificial intelligence offers objective data analysis for complex biological samples.
Purpose of the Study:
- To review recent advancements in artificial intelligence for semen analysis.
- To explore AI's potential in addressing semen analysis challenges.
- To highlight AI's role in male infertility diagnosis and treatment.
Main Methods:
- Systematic literature search of the PubMed database.
- Inclusion of human-related studies, excluding non-English articles, abstracts, case reports, and meeting reports.
- Extraction of data on AI algorithms used for semen parameter evaluation.
Main Results:
- Initial search identified 306 articles; 225 were excluded.
- Full-text review of 81 articles led to the exclusion of 48 more.
- A final 33 original articles were included in the review.
Conclusions:
- AI and machine learning are increasingly utilized in biomedical fields.
- AI algorithms can significantly aid andrologists and embryologists in sperm examination.
- Future improvements in AI accuracy are expected with larger, more reliable datasets.
