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AI in Ultrasound Follicular Monitoring Moves Toward Clinical Decision Support – RBMO
RBMO/LinkedIn
Apr 30, 2026, 18:45

AI in Ultrasound Follicular Monitoring Moves Toward Clinical Decision Support – RBMO

Reproductive BioMedicine Online (RBMO) shared a post on LinkedIn:

“The role of AI in follicular monitoring has evolved from a technical option to an essential pathway for advancing standardization and accessibility in reproductive medicine.

This Commentary from Chenke Kuang, Zichao Liu, Yiyang Huang, Yaocheng Xiao, Meng Du,and  Zhiyi Chen unpacks the developmental pathway of artificial intelligence (AI) in ultrasound follicular monitoring, to define the current paradigm shift from automated segmentation to clinical decision support.

Through deeper integration with clinical devices and continuous algorithmic iteration, intelligent ultrasonography systems are poised to become an indispensable component of the assisted reproduction workflow, providing reliable support for more efficient, precise and individualized patient diagnosis.

This article presents a timely and clinically relevant overview of advances in automated folliculometry and artificial intelligence-driven decision support in ovarian stimulation

Read the full Commentary for free from our in-press articles, now.”

Title: AI-driven paradigm shift in follicle ultrasound monitoring: from automated segmentation to clinical decision support

Authors: Chenke Kuang, Zichao Liu, Yiyang Huang, Yaocheng Xiao, Meng Du, Zhiyi Chen

AI in Ultrasound Follicular Monitoring Moves Toward Clinical Decision Support – RBMO

AI Chenke Kuang Fertility Fertility News Meng Du RBMO Reproductive BioMedicine Online reproductive health Reproductive Medicine Yaocheng Xiao Yiyang Huang Zhiyi Chen Zichao Liu
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