Solution
"Early detection with continuous data
reduces hospitalization by up to 35%"
- Lancet Digital Health, 2023 -
DeepHealthNet
The current healthcare system often faces strain due to late diagnoses and inefficient resource allocation - AI prediction addresses these issues by enabling early detection and prioritizing urgent cases, ultimately improving patient outcomes and reducing costs.
We provide a range of AI-driven solutions that seamlessly and continuously collect health- related data from users' daily lives. This data is then accumulated in time-series format to build a personalized health big data record. Using DeepHealthNet, we analyze these records to predict individual changes across key health indicators, enabling timely intervention and supporting preventive healthcare tailored to each person.
Big-data Analysis
Beyond isolated snapshots — we analyze time-series patterns by segment behavior.
Early Alert
Predictive insights based on big data to flag risks before symptoms appear.
Early Prevention
Act early to reduce risk, cost, and inefficiency — powered by AI prediction.
How It Works
STEP 1
Data Consolidation
Time-series data collected or received to form health big data
STEP 2
Pattern Segmentation
AI clusters personal data into segments by health pattern types
STEP 3
Predictive Modeling
Trained models forecast likely health changes from data trends
STEP 4
Proactive Insights
Future changes are predicted to enable early action, not late response
DeepHealthVision
The human body naturally emits a variety of signals that reflect its health status. By observing these signals, we can evaluate an individual's condition, detect potential issues, and proceed with appropriate management or treatment. However, capturing these signals has traditionally required expensive medical devices—often limited by time, cost, and location.
We empower individuals to easily measure these vital signals in everyday life through DeepHealthVision, our AI-powered solution. As long as a device has a camera and internet connection, users can monitor key indicators such as blood pressure, heart rate, blood glucose, and skin condition—anytime, anywhere—enabling proactive responses to changing health conditions.
Everyday
No dedicated device required — just use your mobile, tablet, or PC to measure your daily bio-signals.
Anytime
No visit or wait needed — 30-second real-time vital scan with DeepHealthVision.
Anywhere
No need for trained staff or nurses — works from home or office by AI, enabling real-time diagnosis & intervention.
How It Works
STEP 1
Scan Your Face
Scan your face with a camera on an Internet-connected device
STEP 2
AI Process
Preprocess rPPG data, extract BVP, then calculate and estimate the health Indicators
STEP 3
Real-time Result
Delivers real-time vital signs and health status across 20+ indicators
STEP 4
Trend & Prediction
Time-series trends and predictive insights for early health intervention
Would U Do It! (WUD!)
WUD! is a solution designed to help children and adolescents build healthy habits from an early age by engaging them in enjoyable, game-like services that encourage voluntary and consistent participation in health management. We currently provide WUD! for two types of health management - obesity care and mind care - that use gamified healthcare experiences to support both physical and mental well-being (Additional health management services will be launched continuously). Through these services, we collect time-series daily personal health records (PHR) to predict health changes and provide personalized management, enabling early identification of symptoms and potential health issues. At the same time, we provide caregivers—including parents, communities, B2G, and B2B partners—with data reports and an administrative system to support early offline intervention and treatment at the community level.
Gamification
Using game elements to promote continuous usage among children and adolescents.
Data-driven Solution
Providing personalized health solutions and supporting healthy habit formation through AI-based data collection and analysis.
Online-to-Offline
Linking online health tracking to offline medical care through early identification of symptoms, warning alerts, and caregiver collaboration.
How It Works
STEP 1
Data Collection
Collects children’s health data — including daily activities, sleep patterns, nutrition, and stress — through engaging gamified content.
STEP 2
Integrated Monitoring
Real-time health indicator tracking and AI-based analysis of personal health records, behavioral patterns, emotional stability, and stress levels.
STEP 3
Personalized Care
Offers personalized health goals along with proactive risk detection and tailored preventive recommendations for better well-being.
STEP 4
Integrated Management
Provides connection to offline specialist consultations and personalized treatment programs whenever professional care is needed.
