Dr. Michelle Lo is CEO and Co-founder of AxileLife Limited and a Postdoctoral Research Fellow at the Advanced Biomedical Instrumentation Centre, The University of Hong Kong. She earned her Bachelor's degree in Medical Engineering from HKU in 2019 and completed her PhD in 2023, specializing in deep learning applications for biomedical imaging. Dr. Lo's research focuses on developing AI-powered imaging algorithms for high-throughput quantitative phase imaging and batch effect correction in large-scale cellular analysis. Her work has been published in premier journals including Advanced Science and recognized with multiple Best Paper/Presentation Awards at SPIE Photonics West BIOS (2021-2023) and the International BME Symposium (2024). She holds one pending US patent on generative deep learning for biomedical image standardization. At AxileLife, Dr. Lo leads the development of AI-enhanced assisted reproductive technologies, bridging advanced imaging science with clinical healthcare innovation.

Transforming Fertility Care: AI-Driven Innovation in Assisted Reproductive Technology (ART)

Assisted Reproductive Technology (ART) has revolutionized fertility treatment, yet significant challenges persist in embryo selection, sperm assessment, and overall treatment success rates. Current ART practices rely heavily on subjective morphological evaluation and standardized protocols that often overlook individual patient variations, leading to suboptimal outcomes and prolonged treatment cycles. The integration of artificial intelligence with advanced biomedical imaging presents a transformative opportunity to address these limitations and elevate fertility care from art to precision medicine.

This presentation introduces a novel Intelligent Reproductive Technology (IRT) framework that synergistically combines high-throughput quantitative phase imaging, microfluidic systems, and deep learning algorithms to enable objective, standardized, and personalized fertility assessment. Our platform addresses three critical gaps in current ART: eliminating operator-dependent variability in gamete evaluation, providing real-time quantitative cellular analysis without invasive labeling, and generating predictive insights that guide individualized treatment strategies.

We will showcase technological breakthroughs across advanced imaging capabilities for label-free cellular profiling, microfluidic innovations for gentle sample handling, and AI models validated on large-scale clinical datasets. These achievements have translated into clinical-ready products currently undergoing implementation at Queen Mary Hospital, Kwong Wah Hospital, and HKU-Shenzhen Hospital, with our AI-powered sperm fertility assessment system launching by year-end 2025.

As healthcare systems increasingly adopt electronic health records and interoperable digital infrastructure, AI-enhanced fertility care represents a crucial evolution—moving cutting-edge technology from novelty to necessity. This integration promises not only improved clinical outcomes but also establishes a foundation for data-driven reproductive healthcare that aligns with broader eHealth ecosystem development across the Asia Pacific region.