Dataset-Driven Voice Biomarker Validation: Advancing Clinical Standards with the Enhanced V3 Framework

Abstract

Advancements in information technologies are reshaping the medical field, highlighting the need for effective frameworks to translate research into clinical practice. Voice is a promising biomarker for disease detection, but its use is limited by the lack of rigorous clinical validation methods. Our research aims to bridge this gap by improving the validation process for voice-based health assessments. Building on our clinical trial experience and the V3 framework, we are enhancing it to address the specific challenges of voice biomarkers, focusing on the data life-cycle in trials. Our proposal involves refining the V3 framework and developing an open-source toolkit for evaluating voice-based health datasets, bridging the gap between research and clinical practice through robust validation.