Early Detection of NEC — 10 Hours Before Symptoms
Some babies are born too early. Their bodies are still fragile — especially their intestines. Sometimes, a dangerous infection called NEC attacks their gut silently, with no warning signs. By the time doctors notice, it can be too late. Enayah watches their heartbeat, temperature, and oxygen levels every single hour — and warns the nurse 10 hours before anything looks wrong.
An AI-powered clinical decision support system built on XGBoost, monitoring premature infants in NICU 24/7 — no new hardware required.
A Silent Threat in Saudi NICUs
Silent disease destruction
NEC progresses without visible symptoms until severe damage occurs.
Late detection
Traditional methods rely on visible clinical signs that appear too late.
Irreversible damage
By the time NEC is identified, intervention is often too late to save tissue.
By the time a nurse detects NEC through traditional methods, the damage may already be irreversible.
Sources: King Faisal Specialist Hospital & Research Centre, Riyadh — 7.5% NEC in VLBW infants ≤1500g (2006–2008, n=186); 9.1% NEC in preterm VLBW infants 400–1500g, GA 23–32 wks (2006–2015, n=528). King Saud University Medical City, Riyadh — 16% NEC in preterm infants <1500g and <33 weeks (2011–2018, n=512). A nationwide Saudi NEC percentage has not been established; reported single-center NICU rates range from ~7.5% to 16%.
Continuous AI-Powered Vigilance
↔ Drag the slider to compare NICU before & after Enayah
Continuous Monitoring
Reads vital signs (heart rate, temperature, oxygen) every hour from existing NICU equipment.
XGBoost AI Model
Compares real-time data against thousands of historical NEC cases to generate a risk score.
Instant Alert
Sends an immediate notification to the nurse's dashboard when risk threshold is exceeded.
Less than 1 false alarm per patient per week. The nurse stays in control — Enayah ensures she looks at the right time.
Four Steps. Continuous. Automatic.
Auto-Collect Vitals
NICU devices auto-collect vitals every hour (HR, Temp, SpO₂).
Pattern Shift
Vital sign patterns shift hours before NEC symptoms appear.
AI Risk Score
XGBoost model compares data to prior NEC cases and outputs a risk score.
Instant Alert
System sends instant alert to nurse dashboard when threshold is exceeded.
Inside the Model
The Smart Choice for Clinical AI
| Feature | Our Choice XGBoost | Random Forest | Neural Network | Logistic Regression |
|---|---|---|---|---|
| Accuracy on clinical data | ★★★★★ | ★★★★ | ★★★★ | ★★★ |
| Speed & efficiency | ||||
| Handles missing data | ||||
| Interpretability | ||||
| Proven in NEC studies | 97% (stacking) | |||
| Works with small datasets |
XGBoost has been validated in multiple NEC/sepsis studies achieving up to 97% accuracy in stacking classifiers (Robi et al., 2023), and delivers real-time hourly risk scores with 10-hour advance warning (Meeus et al., 2024).
Saving Lives, By the Numbers
Early medical intervention prevents permanent damage
Families informed earlier for psychological peace of mind
NICU team monitors all patients simultaneously
Scientifically validated through peer-reviewed research
Built for Every NICU
Government Hospitals (MOH)
Kingdom-wide deployment
Private Hospitals
Premium NICU care
University Hospitals
Research & validation partner
Neonatal Sepsis
Same vital-sign monitoring pipeline
Remote NICUs
Low-resource settings, no new equipment
Clinical Research
Real-time data for NEC studies
Tailored to Your Hospital
Basic
Every hospital is unique — pricing is tailored based on your NICU size, scale, and subscription tier.
- 1 NICU unit
- Alerts dashboard
- Monthly reports
Professional
Every hospital is unique — pricing is tailored based on your NICU size, scale, and subscription tier.
- Multi-ward coverage
- EHR integration
- Real-time analytics
Enterprise
Every hospital is unique — pricing is tailored based on your NICU size, scale, and subscription tier.
- Nationwide deployment
- API access
- Dedicated support
Builders of Enayah
Thabit Al-Malki
Specialized in project management and quality assurance
Amr Issa
Enayah NEC early detection system