The National Science Foundation (NSF) has awarded TQIntelligence with a Small Business Innovation Research (SBIR) Phase I grant to further develop its machine learning (ML) algorithm that detects clinically relevant emotional distress in speech samples from at-risk youth.
The $225,000, six-month grant supports Atlanta-based TQIntelligence’s effort to leverage human voice/speech to develop a voice biomarker of psychological distress in children and adolescents. TQIntelligence is a health technology company in the Advanced Technology Development Center’s ATDC Accelerate portfolio.
“Receiving this Phase I grant is an important milestone for us and a critical component of our building one of the most extensive and comprehensive clinical voice sample data sets to develop voice biomarkers that quantify and predict emotional disorder severity of at-risk youth,” said Dr. Yared Alemu, TQIntelligence’s founder and Clinical Director.
Clarity AI, TQIntelligence’s scalable patient-centered digital health platform, is intended to improve the timely and accurate assessment of behavioral/emotional disorders.
The analytic solutions are designed to help mental health professionals and other healthcare providers working with children and adolescents to identify emotional disorder severity early and efficiently, and track treatment progress and outcomes systematically.
“The mental health system of care is mostly devoid of systemic data, and decisions about care are qualitative and subjective,” said Sandeep Yadav, CEO of TQIntelligence. “We are focused on transforming this system in close collaboration with healthcare providers and payers.”
By improving the timely and objective measurement of mental health issues in children and adolescents using innovative technology, TQIntelligence aims to help healthcare providers and payers, such as Medicaid Managed Care, meet the triple goal of improving patient care, quality, and experience at a lower cost.
Headquartered in Atlanta, Georgia, TQIntelligence is focused on transforming behavioral healthcare services for at-risk youth by leveraging cutting edge technologies in digital health, artificial intelligence (AI), and automation. We use voice recognition technology and AI to quantify and predict mental health disorder severity for at-risk youth to improve treatment outcomes.