Speaker Profile
Ph.D., Chief Data Scientist, HopeAI
Biography
Maggie Wang is the Chief Data Scientist at HopeAI, where she leads the development of advanced data curation systems designed to transform unstructured healthcare records into regulatory-quality evidence. With over four years of experience processing millions of life-science records, Maggie specializes in high-precision knowledge extraction from complex clinical data. Her work at HopeAI is instrumental in bridging the gap between raw data and actionable intelligence, enabling more precise clinical development and treatment decisions for the next generation of precision medicine.
Talk
Generating Regulatory-Quality Evidence for Precise Clinical Decisions
Clinical decisions often lag behind the latest evidence. Validated in partnership with Mayo Clinic and Fred Hutch, HopeAI’s PURE Evidence agentic workflow achieved significantly higher accuracy in oncology, outperforming general LLMs and RAG systems. Learn how HopeAI transforms unstructured data into regulatory-quality evidence to bridge the evidence-practice gap.
AI for Clinical Decision Support Systems Showcase:
HopeAI
HopeAI bridges the gap between clinical depth and statistical innovation, delivering the evidence-driven insights needed to transform drug development and patient care.
Session Abstract – PMWC 2026 Silicon Valley
The PMWC 2026 AI for Clinical Decision Support Showcase will provide a 15-30 minute time slot for selected organizations, including commercial companies, clinical testing labs, and medical research institutions, to present their latest advancements, insights, applications, and technologies to an audience of clinicians, leading investigators, academic institutions, pharma and biotech, investors, and potential clients. We will learn about new technologies and findings that promise expedited, cost-effective, and accurate clinical diagnosis for early disease detection, treatment decisions, and disease prevention.
