Discover how combining computational analysis with human insights creates more accurate, patient-centered healthcare research. This session explores the limitations of purely algorithmic approaches to analyzing patient-generated content online and demonstrates a novel mixed-methods solution that integrates social science with data science.
Using a real-world case study on medicated weight loss, we'll show how surveys, interviews, and expert perspectives can refine computational models to overcome silent gaps, misclassification, and structural bias in digital health data. Learn what this means for strategic decision-making in healthcare, government, and pharmaceutical industries.
The event includes an opportunity for individuals currently using GLP-1 medications like Ozempic to participate in voluntary, confidential interviews, contributing directly to ongoing research while seeing how their lived experiences shape data-driven insights.
Ideal for AI practitioners, data scientists, healthcare researchers, industry professionals, and community members with relevant health experiences.
