Artificial Intelligence as an Assistant in management of Male-Factor Infertility
Code: G-1137
Authors: Zahra Khalaj ℗, Behnaz Banimohamad-Shotorbani, Vahideh Shahnazi, Maryam Ghahremani-Nasab, Hekmat Farajpour *
Schedule: Not Scheduled!
Tag: Biomedical Signal Processing
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Abstract:
Abstract
Background and Aims : Infertility is a significant issue for millions of couples. In our society, it affects all aspects of life, the most important being mental health. Male factor infertility can be a health concern for men and is primarily responsible for the inability to conceive a child after a year of regular, unprotected intercourse. In recent years, artificial intelligence (AI) has played an extensive role in medical sciences, particularly in the diagnosis and treatment of various diseases. It has also shown great potential in different aspects of male infertility. One of the major infertility issues in men is reduced sperm count caused by varicocele, along with abnormal sperm shape and movement. Methods: AI is revolutionizing the approach to male infertility by improving the analysis of sperm quality and morphology. AI algorithms can process large datasets quickly, allowing for more precise assessments of sperm characteristics, which are crucial for successful fertilization. One significant application of AI in this field is the use of deep learning techniques to analyze sperm images. These algorithms can classify sperm based on morphology, motility, and viability, providing insights into male fertility potential. For example, a study by Esteves et al. demonstrated that AI models can predict sperm DNA fragmentation and correlate it with reproductive outcomes, thereby guiding clinical decisions in assisted reproductive technologies (ART). Results For the first time, Kruger and his team identified a link between egg fertilization and sperm shape. Research indicates that normal sperm morphology contributes to successful fertilization and can enhance live birth rates in IVF and ICSI procedures. Utilizing deep learning and machine learning, AI can effectively visualize and classify the sperm's head, tail, and midpiece. These algorithms analyze sperm morphology quickly and accurately. Conclusion AI acts as a powerful tool that complements the expertise of specialists, ultimately leading to better management of male infertility.
Keywords
Artificial Intelligence, Male-Factor Infertility, Sperm Analysis
