Machine Learning Evaluation of Semen Analysis Could Reveal New Infertility-Related Markers: A Pilot Study
This pilot study applies machine learning to two extensive datasets, suggesting that changes in semen analysis may be linked to other variables, such as testicular ultrasound characteristics, red blood cell count, and environmental pollution.
Authors
- Daniele Santi (ORCID: https://orcid.org/0000-0001-6607-7105)
- Carlotta Pozza (ORCID: https://orcid.org/0000-0002-1147-6114)
- Laura Roli (ORCID: https://orcid.org/0000-0001-7154-189X)
- Maria Cristina De Santis (ORCID: https://orcid.org/0000-0002-2169-3921)
- Daniele Gianfrilli (ORCID: https://orcid.org/0000-0002-2682-8266)
- Giorgia Spaggiari (ORCID: https://orcid.org/0000-0002-7089-7330)
- Marco Bonomi (ORCID: https://orcid.org/0000-0001-5454-6074)
- Tommaso Trenti (ORCID: https://orcid.org/0000-0001-8093-4011)
- Manuela Simoni (ORCID: https://orcid.org/0000-0002-2133-4304)
- Emilia Sbardella (ORCID: https://orcid.org/0000-0002-2220-9783)
- Donatella Paoli (ORCID: https://orcid.org/0000-0002-9699-8703)
- Andrea Maria Isidori (ORCID: https://orcid.org/0000-0002-9037-5417)
Institutions
- University of Modena and Reggio Emilia (IT)
- University of Milan (IT)
- Azienda Unita' Sanitaria Locale Di Modena (IT)
- Azienda Ospedaliero-Universitaria di Modena (IT)
- IRCCS Istituto Auxologico Italiano (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- The World Journal of Men s Health
- Published
- 2025-01-01
- DOI
- https://doi.org/10.5534/wjmh.250096
- Primary Topic
- Sperm and Testicular Function
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministero dell’Istruzione, dell’Università e della Ricerca