Healthcare Intelligence Software based on Vocal Biomarkers
What if we could use technology to enable a cost-effective, fast and reliably prevention, treatment monitoring and corona lifecycle management based on real-time health data and shift Corona Treatment from reactive to proactive?
While the mobilization of the healthcare system is underway, measures have been adopted in Germany and many other countries around the world to dramatically reduce the number of new infections – with unprecedented far-reaching consequences for civil liberties and the economy in our democratic economy.
Due to its characteristics (often asymptomatic, highly infectious, long incubation periods), the COVID 19 pandemic places the healthcare system, the economy and the individual liberty rights in our society under a stress test unprecedented in our globalised and highly technological world. In view of the effects of the containment measures, there is a need for a considerably improved data basis that provides information on the spread of the disease in the population. A location-independent, cost-effective and rapid testing method for COVID-19 of a broad part of the (world) population is needed to effectively monitor the spread of COVID-19 and to enable the consequences associated with disease control through targeted lifecycle management by health authorities.
We need a fast, cost-effective and reliable Healthcare Intelligence Testing for the early detection of respiratory viral diseases and public health surveillance software that go beyond the state of the art for detection of COVID-19.
We need to use daily-life technology that is widespread and cost-effective for early detection of viral diseases based on easily detectable digital biomarkers (especially audio streams), which can be used and accepted by large parts of the world’s population, and enables fully digital lifecycle management.
Democratization of COVID-19 Testing and Tracking based on Artificial Intelligence
We develop an AI-based Healthcare Intelligence Software for the early detection of COVID-19 symptoms based on digital biomarkers. By means of a location-independent pattern recognition in voice streams (so called Vocal Biomarkers), probabilities of a COVID-19 infection will be calculated and health authorities and clinics will be supported by artificial intelligence to identify COVID-19 symptoms independently of location on the basis of digital and especially so-called vocal biomarkers (= voice, breath and cough noise samples).
Vocal biomarkers have the potential to revolutionize diagnostics through their accuracy, speed and cost efficiency and are currently being tested especially in the field of mental diseases as well as physical diseases such as Parkinson’s or coronary artery disease. Evidence is mounting that a number of mental and physical conditions have an influence on tone of voice, choice of words and sounds.
Clinical Study on COVID-19 testing based on vocal biomarkers
We therefore conduct a clinical study on the efficacy of vocal biomarkers for the early detection of COVID-19, which has the potential to revolutionize COVID-19 diagnostics through its accuracy, speed and cost-effectiveness. If the research hypothesis proves to be true, this would represent a breakthrough in the field of social prediction and location-independent early diagnostics.
Technology Transfer of the Research Results in Healthcare Intelligence Software
For the transfer of the research results, we intend to develop in parallel an AI-based Healthcare Intelligence Software based on digital biomarkers to control the lifecycle management of COVID-19 disease in the population by health authorities and hospitals. At validation of the research hypothesis, it also includes vocal biomarkers.
By means of COVID-19 pattern recognition in voice streams (speech, breathing and coughing sounds), the probabilities of a COVID-19 infection are to be calculated quickly, cost-effectively and location-independently using commercially available smartphones.
Health authorities and clinics worldwide would thus be able to identify COVID-19 symptoms quickly, inexpensively and independently of location through broad-based testing of the population and AI-supported early diagnosis. This would enable health authorities to improve the accuracy of testing and treatment by locating the patient in the life cycle of COVID-19 disease, relieve the burden on the medical care system through targeted treatment control and enable health authorities to monitor the course of the pandemic more specifically. In the long term, this would also make it conceivable to use the system for early detection of atypical epidemic scenarios by random and anonymous evaluation of environmental noise in public spaces.
Improvement of the accuracy of testing and treatment by locating the patient in the life cycle of COVID-19 disease
Relief of the medical care system through digital biomarker-based self-test app
Improvement of the lifecycle management and tracking of healthcare workers' infections in pandemic scenarios through more targeted, digital and biomarker-based surveillance of disease progression
Democratization of COVID-19 testing in regions and countries with less developed health systems by using everyday technologies
Support of medical diagnosis of COVID-19 by AI-based detection of digital biomarker-based early indicators
More targeted management of medical care and testing in viral diseases through continuous patient monitoring
Monitoring of the active and passive immunization through targeted lifecycle management
Early detection of atypical epidemic scenarios through random and anonymous evaluation of environmental noise in public spaces and waiting areas
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