Predicting Psychological and Blood Age to Reduce Stress

Goal

Predicting Psychological and Blood Age to Reduce Stress

Synaptron created deep learning models to assess psychological and biological aging. One model predicts psychological age and recommends stress-reducing actions, while another computes “blood age” using automated blood report analysis. These aging clocks help users manage stress through personalized insights and are now available in the market.

Industry: Healthcare
Technology: Deep Learning
Client: UK-based

Challenge

The client needed a system to assess psychological and biological aging for stress management, providing personalized recommendations for users based on their health profiles.

Solution

Synaptron developed two deep learning models. The first model predicts psychological age based on responses to stress-related questions and generates personalized recommendations to lower stress and psychological age. The second model calculates “blood age” by analyzing parameters extracted from users’ blood reports, which are parsed automatically by a PDF reader.

Impact

These innovative aging clocks were successfully launched in the market, offering users a personalized approach to wellness. The dual-system solution provides insights into biological and psychological health, aiding users in stress management and promoting a balanced lifestyle.

Results

Enhanced user engagement with personalized recommendations
Data-driven stress management insights
Improved accessibility to health analytics through automated report parsing