Bridge2AI-Voice: Advancing Clinical AI Through Ethically Sourced Voice Biomarkers

Presentation Type: Panel
Presentation Time: 08:00 AM - 09:15 AM

Abstract Keywords: Ethics, Analytical Artificial Intelligence: ML, Digital Pathology, Imaging AI, Predictive Analytics, Governance, Education and Training, Precision Medicine, Multi-Omics, and Pharmacology Integration
Primary Track: Big Data for Health


Voice is emerging as a powerful, non-invasive biomarker that supports early disease detection, monitoring, and personalized care. The ubiquity of ambient listening technologies, ranging from smartphones and telehealth platforms to wearables and clinical monitoring systems, creates new opportunities to capture real-world voice data at scale. As these data streams expand, it becomes increasingly important to develop trustworthy, clinically grounded AI models that can responsibly leverage voice signals while safeguarding privacy and equity. The NIH-funded Bridge2AI-Voice consortium is building one of the largest clinically validated, ethically sourced voice datasets to date, integrating audio recordings with phenotype and clinical metadata across multiple disease domains. This panel brings together leaders in clinical informatics, translational AI, and workforce development to discuss how the consortium’s standards, training programs, and governance frameworks prepare the field for a future where voice-derived insights can augment screening,

Moderator:
Philip Payne, PhD, FACMI, FAMIA
WashU Medicine and BJC Healthcare

Speaker(s):
Andrea Krussel, MA
Washington University in St. Louis

William Hersh, MD, FACMI, FAMIA
Oregon Health & Science University

Phillip Jenkins, MD
Oregon Health & Science University

Author(s):
Andrea Krussel, MA - Washington University in St. Louis; Philip Payne, PhD, FACMI, FAMIA - WashU Medicine and BJC Healthcare; William Hersh, MD, FACMI, FAMIA - Oregon Health & Science University; Phillip Jenkins, MD - Oregon Health & Science University;

---