'Beyond Verbal' Hopes to Assess Medical Conditions Through Voices
References: beyondverbal & digitaltrends
Some say that the quality of one's voice communicates just as much as the words spoken, and Beyond Verbal has built its entire platform around that tenet. The company uses machine learning, big data analysis and vocal samples to assess people's emotional states based on their voices. And now, in a collaboration with the Mayo Clinic, Beyond Verbal is working to extend its platform to include medical conditions like clinical depression and heart conditions.
Though the technology is currently too imprecise to be effective as a primary diagnostic tool, it is already very effective as a way to monitor health over time. For instance, if a patient is suffering from a diagnosed condition, doctors can use Beyond Verbal's platform to check on the progression of that condition weeks or months after the initial diagnosis.
Though the technology is currently too imprecise to be effective as a primary diagnostic tool, it is already very effective as a way to monitor health over time. For instance, if a patient is suffering from a diagnosed condition, doctors can use Beyond Verbal's platform to check on the progression of that condition weeks or months after the initial diagnosis.
Trend Themes
1. Voice Analysis - Opportunity for using voice analysis technology to assess emotional states and medical conditions.
2. Machine Learning - Application of machine learning in analyzing vocal samples for health monitoring and diagnostic purposes.
3. Big Data Analysis - Utilizing big data analysis to identify patterns and correlations between voice features and medical conditions.
Industry Implications
1. Healthcare - Integration of voice-analyzing technology in healthcare for assessing emotional states and monitoring medical conditions.
2. Technology - Use of voice analysis and machine learning in the development of innovative solutions for healthcare and wellness industries.
3. Data Analytics - Application of big data analysis techniques for extracting valuable insights from vocal samples in healthcare settings.
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