Using ML for Voice-based Biomarkers

We collaborated with a pioneering digital health company specializing in voice-based biomarkers and assays. Our mission was to devise intricate design strategies for online assessments that culminate in comprehensive reports for laboratories and healthcare providers, marking a significant advancement in the field of life sciences.

Project Overview

This client was looking to develop an intuitive user-interface for online surveys to collect voice and video samples that could be processed in a microservice architecture. Their goal was to address the complex needs of their life science customers. As a trusted technology partner, we were instrumental in architecting and implementing a solution that streamlined sample collection and facilitated advanced data analysis.

Solutions

• Interactive Survey Interface: Leveraged React to craft a custom interface for survey collection, incorporating WebRTC for high-quality voice and video capture.
• Scalable Processing Architecture: Established a microservice architecture using NodeJS and Python within Kubernetes, ensuring efficient management and processing of voice samples.
• Dynamic Data Streaming: Implemented Kafka for real-time voice sample streaming into a data pipeline, enabling comprehensive feature extraction and analysis across numerous processing jobs.
• Advanced ML Feature Classification: Utilized Python’s ML and AI libraries to accurately classify features derived from the voice samples, tapping into the vast potential of machine learning.
• Assessment Report Redesign: Undertook a significant redesign of the assessment reports provided to life science labs and healthcare providers, enhancing readability, accessibility, and the presentation of complex data insights.

Impact and Outcomes

The project’s success was marked by several key achievements:

• Revenue Growth: Facilitated a 10X increase in revenue, demonstrating the platform’s efficacy and market impact.
• Survey Collection Efficiency: Significantly improved the survey response rate, amassing thousands of submissions and enriching the analytical dataset.
• Facilitated Acquisition: Supported the client through a seamless acquisition process by Sonde Health, heralding a new era for their technology.

Moving Forward

This collaboration highlights the transformative power of AI and machine learning in digital health, especially in analyzing voice-based biomarkers. Looking ahead, the foundation set by this project not only advances life science research but also opens avenues for further innovation in healthcare diagnostics and personalized treatment approaches.