This startup develops AI-powered digital tools for psychiatric care, offering gamified assessments and digital biomarkers for precise evaluations and objective data collection. Their platform enables continuous monitoring and mechanism-based diagnostics, helping mental health professionals tailor treatment approaches and implement measurement-based care.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional psychiatric evaluations rely heavily on subjective assessments and overt symptoms, potentially overlooking the underlying mechanisms of mental health disorders. This can lead to imprecise diagnoses, hindering the ability of mental health professionals to tailor treatment approaches effectively. The lack of objective data and continuous monitoring also limits the ability to implement measurement-based care and track treatment progress accurately.
Solution
TiliaHealth offers an AI-powered platform that delivers digital tools for enhanced psychiatric care, focusing on providing novel digital biomarkers of the mechanisms behind core symptoms of depression. The platform leverages immersive experiences with advanced computational models of psychiatric symptoms to enable mechanism-based assessment anytime, anywhere. By focusing on underlying mechanisms rather than just overt symptoms, mental health professionals can achieve a more precise understanding of an individual's condition. This approach guides more tailored treatment approaches, enables measurement-based care, saves time, decreases costs of treatment, and improves the quality of life for patients.
Target Audience
The primary target audience includes mental health professionals seeking precise evaluations, objective data collection, and continuous monitoring capabilities for their patients, as well as pharmaceutical companies looking to improve patient stratification in drug development.
Features
- Gamified assessments of symptoms of mental health disorders
- AI-powered digital biomarkers of mechanisms behind core symptoms of depression
- Immersive experiences with advanced computational models of psychiatric symptoms
- Continuous monitoring capabilities for tracking patient progress
- Objective data collection for more precise evaluations
- Mechanism-based diagnostics for personalized treatment approaches