Potential for artificial intelligence in medicine and its application to male infertility

生殖医学 不育 男性不育 妇科 医学 生物 怀孕 遗传学
作者
Hideyuki Kobayashi
出处
期刊:Reproductive Medicine and Biology [Wiley]
卷期号:23 (1)
标识
DOI:10.1002/rmb2.12590
摘要

Abstract Background The third AI boom, which began in 2010, has been characterized by the rapid evolution and diversification of AI and marked by the development of key technologies such as machine learning and deep learning. AI is revolutionizing the medical field, enhancing diagnostic accuracy, surgical outcomes, and drug production. Methods This review includes explanations of digital transformation (DX), the history of AI, the difference between machine learning and deep learning, recent AI topics, medical AI, and AI research in male infertility. Main Findings (Results) In research on male infertility, I established an AI‐based prediction model for Johnsen scores and an AI predictive model for sperm retrieval in non‐obstructive azoospermia, both by no‐code AI. Conclusions AI is making constant progress. It would be ideal for physicians to acquire a knowledge of AI and even create AI models. No‐code AI tools have revolutionized model creation, allowing individuals to independently handle data preparation and model development. Previously a team effort, this shift empowers users to craft customized AI models solo, offering greater flexibility and control in the model creation process.

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