Artificial Intelligence Role in IVF and Reproductive Medicine
VerifiedAdded on  2022/07/28
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Report
AI Summary
This report provides an overview of the application of Artificial Intelligence (AI) in reproductive medicine, focusing on its potential to improve in vitro fertilization (IVF) outcomes and address current challenges. It discusses the use of AI and machine learning (ML) in various aspects, including sperm and embryo selection, optimization of ovarian reserve parameters, and analysis of patient outcomes. The report highlights the advantages of AI in image analysis, error reduction, and efficiency improvement, while also acknowledging the limitations, such as data bias, lack of standardization, and data privacy concerns. The report also explores potential solutions like data hubs and federal learning to address these challenges, emphasizing the importance of high-quality data for AI model development. The limitations of the current research in the integration of the analysis of obtained data are also discussed, and the need for more research in diagnosis, treatment, and automatic reproduction is highlighted. Furthermore, the report touches upon the significance of data privacy and governance in healthcare, particularly the use of federal learning (FL) as a solution that enables algorithms training without the exchange of datasets. Overall, the report emphasizes the need for more research and data sharing to unlock the full potential of AI in reproductive medicine.
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