Brooklyn Health
This digital health platform provides a library for digital phenotyping, offering standardized methods for quantifying behavior and measuring mental conditions. It enables academic researchers to integrate these methods into their studies, bridging the gap between research and digital health applications.
- Artificial Intelligence
- Digital Health
- Healthcare Technology
- Software Only
Funding
Raised to date
$6.5MRaised 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
Current methods for assessing mental health conditions often lack standardization, leading to variability in data collection and hindering the development of targeted treatments. Traditional approaches may also be subjective and lack the sensitivity needed for precision neuroscience research and clinical care.
Solution
Brooklyn Health offers a digital health platform designed to standardize mental health measurement through digital phenotyping. Their eCOA (electronic Clinical Outcome Assessment) solution, Willis, employs AI for real-time review of interview quality and score accuracy, ensuring endpoint reliability. The platform enables researchers to integrate objective, sensitive measurement tools into their studies, bridging the gap between research and practical digital health applications. By solving the measurement problem in mental health, Brooklyn Health aims to break down barriers in drug development and pave the way for more effective, personalized care.
Target Audience
The primary target audience includes clinical researchers and pharmaceutical companies involved in CNS clinical trials, as well as healthcare providers seeking objective and reliable tools for mental health assessment and patient care.
Features
- WillisAI: AI-powered engine for real-time review of interview quality and scoring accuracy
- eCOA (electronic Clinical Outcome Assessment) solution for standardized data collection
- Digital phenotyping tools for quantifying behavior and mental conditions
- Speech phenotyping from COA recordings
- LLMs (Large Language Models) to quantify rating quality during clinical scale administrations
- OpenWillis: Measurement of head movement and improvements to existing speech transcription functions
- WillisDiarize: Model to correct speaker labeling errors when analyzing speech in clinical conversations