Xiaoyan

Xiaoyan Wang, PhD, FAMIA

Senior Vice President, Life Science Solutions

Dr. Xiaoyan Wang serves as IMO’s Senior Vice President of Life Sciences Solutions. Prior to IMO, she was the Chief Scientific Officer at Melax Tech. She also previously served as the VP of Healthcare Analytics and Informatics and VP of Biopharma Solutions at GeneDx, where she led the development of clinical evidence generation platforms and clinical research in oncology, immunology, cardiovascular, respiratory, and rare diseases. Dr. Wang is a former faculty member and principal investigator at the University of Connecticut, UConn Health Center, and Mount Sinai Health Systems. She holds a Master of Arts in Genetics from the University of Kansas, and a Doctor of Philosophy in Biomedical Informatics and NLP from Columbia University School of Medicine.

More from Xiaoyan Wang, PhD, FAMIA

During this panel discussion, experts delve into strategies and best practices for efficiently managing and utilizing value set data to enhance the quality of patient care, streamline healthcare operations, and support informed decision-making.
With recent and continued advancements in generative AI in healthcare, many are wondering how it will impact the industry over the coming years. So, what do experts predict?
Melax Tech, now part of IMO, collaborated with Roche in a pilot project led by Stefanie Kaufmann, Roche’s lead data scientist, to address the challenge of extracting structured data from unstructured patient reports in clinical settings.
Guided by industry experts, learn the impact of large language models (LLMs). Explore ChatGPT’s rapid ascent, its role in extracting insights from unstructured healthcare data, and its applications in real-world evidence and clinical trials.
The future of healthcare is intertwined with AI. Dr. Wang shares her insights, experiences, and vision for life science’s next frontier.
Watch Xiaoyan Wang, PhD, Chief Scientific Officer at Melax Tech, now part of IMO, as she takes a deep dive into the cutting-edge advancements in NLP.