Hyfe
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About
Hyfe is an AI-powered respiratory care company using acoustic epidemiology to analyze cough sounds for diagnostics and monitoring. It offers continuous, clinically validated cough monitoring solutions for pharma, academics, and healthcare providers. The platform uses smartphones and wearables to collect data, providing insights into cough frequency and patterns. This data helps detect the onset of illness, monitor disease progression, and assess treatment effectiveness. Hyfe's technology has been used in numerous clinical trials and published research.
Platform
Task
Features
• ai-powered analysis
• continuous cough monitoring
• longitudinal data analysis
• personalized baselines
• works in diverse environments
• scalable across devices
• privacy preserving (on-device processing)
FAQs
What is Hyfe?
Hyfe is an AI company that uses acoustic epidemiology to analyze health sounds, primarily coughs, for health measurement, outbreak detection, and disease diagnosis. It offers tools for remote patient monitoring, digital biomarkers in clinical trials, and more.
I need cough detection in my research. How do I get started?
Submit a request to begin a research cohort. Hyfe will contact you to discuss and share instructions.
How has Hyfe solved the cough detection problem?
Hyfe uses AI models that run passively and privately, detecting coughs unobtrusively. It works on any smart device with a microphone.
What other AI powered cough analysis approaches exist?
Single-cough analysis models analyze a sample of coughs for structural signals, but this has limitations in biological plausibility, infrastructure, costs, and scalability. Hyfe offers a superior alternative. More details can be found in a linked analysis.
How is the training data for cough detection AI models collected and used?
Hyfe's models are trained on a massive dataset of coughs from diverse environments and demographics. It uses medically validated data from 46+ IRB-approved research trials, providing high-quality data for training.
What are the privacy and security considerations for continuous cough monitoring models?
Hyfe's models run entirely on the device, ensuring 100% privacy by analyzing only cough timestamps without recording sounds. On-device processing also enhances security.
What are the global health implications and applicability of continuous cough monitoring in low infrastructure settings?
Continuous cough monitoring is scalable via smart devices with no infrastructure dependencies. It's suitable for low-infrastructure settings and useful for public health surveillance and disease outbreak detection.
What devices are compatible with continuous cough monitoring technology?
Hyfe's technology is device-agnostic, working with any device having a microphone (smartphones, wearables, etc.). For research and life sciences, Hyfe offers a proprietary wearable.
Is continuous cough monitoring available for both adults and children?
Hyfe's technology has been used across all age groups; however, the current FDA application is for adults only.
How does continuous cough monitoring ensure accuracy in the real world?
Hyfe's models are trained on a vast, diverse dataset, and rigorous validation trials demonstrate near-perfect performance; contact Hyfe for validation data.
How does continuous cough monitoring handle false positives or negatives?
Advanced algorithms and a large training dataset minimize false positives/negatives. Even occasional errors normalize over time.
Are there any limitations or challenges in deploying continuous cough monitoring at scale?
Unlike single-cough classifiers, Hyfe's models are trained on real-world data, making scaling fast, cheap, and efficient.
What measures are in place to protect patient and user privacy and data security in continuous cough monitoring?
Hyfe's on-device processing ensures enhanced privacy and security with minimal risk of data breaches.
How does continuous cough monitoring adapt to individual variations in cough patterns among patients?
Continuous cough monitoring establishes personalized baselines and adjusts to individual patterns, providing customized insights.
What are the potential future developments in continuous cough monitoring technology?
Future developments include increased sensitivity, integration with smart home devices, and broader applications in personalized medicine and public health. Behavioral cough suppression therapy is a significant development.
Job Opportunities
Project Manager (Research)
Hyfe uses AI to continuously monitor cough, providing insights for respiratory health. It offers solutions for research, clinical trials, and patient care.
Benefits:
Flexible working hours
Workstation support
Employee stock options
Education Requirements:
Degree in Public Health or equivalent experience in research within a clinical setting or public health context
Experience Requirements:
Demonstrated ability to organize, administer, and orchestrate projects involving complex logistics within tight timelines
Excellent team player who also thrives working independently, thinking creatively, and taking initiative to address needs and seize opportunities
Experience in IRB / ethical committees procedures, documentation creation, and clinical study design
Other Requirements:
Energetic, outgoing, charismatic, and someone who thrives in building partnerships and managing relationships
Looking for a career that blends public health science with relationship building
Responsibilities:
Coordinate and support external research partners around the world
Provide ongoing support for all research partnerships
Support research partners in implementing Hyfe research tools in their projects
Manage a portfolio of research partnerships
Launch coordinator for all research partnerships: Primary consultant on IRB approval, clinical research design, and project setup
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