The startup is developing a personalized predictive clinical score that integrates physiological measurements and machine learning to enhance treatment for patients with major depressive disorder and post-traumatic stress disorder. This technology enables physicians to conduct objective clinical monitoring, improving recovery rates and quality of life for outpatients.
Funding
$3.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Patients with major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) often experience relapses and transitions to chronic conditions due to a lack of timely intervention. Current monitoring methods may not provide physicians with sufficient advance warning to proactively adjust treatment plans and prevent these negative outcomes.
Solution
MyndBlue offers a digital MedTech solution that provides physicians with a personalized, predictive clinical score for outpatients with MDD and PTSD. The system combines physiological measurements with artificial intelligence to detect and predict potential issues in real time, enabling earlier intervention. By identifying risks before a relapse occurs, MyndBlue aims to improve treatment success rates and enhance the quality of life for patients. The core technology leverages a machine-learning algorithm designed to provide transparent and trustworthy support for clinical decision-making, even under real-world data conditions.
Target Audience
The primary target audience includes psychiatrists, clinical psychologists, and other healthcare providers involved in the treatment of patients with MDD and PTSD.
Features
- Predictive AI algorithm trained on physiological measurements from MDD and PTSD outpatients
- Personalized clinical score to forecast potential relapses or transitions to chronic conditions
- Real-time monitoring and alerts to enable timely intervention by physicians
- Identification of predictive biomarkers to facilitate precision medicine in mental health
- Integration of patient data to support objective clinical monitoring