Architecture

Below is a high-level architecture sketch showing how OmegaX handles healthcare data, applies AI-driven medical reasoning, and engages with users. We focus on medical workflows—rather than implementation details like programming languages or specific databases.

OmegaX Health Architecture Overview

Key Components

1. Omega Data Feed

   • Collect user metrics (vitals, lab results, EHR data), unify different sources (wearables, clinics, Apple HealthKit, etc.), and pre-process them (unit standardization, timestamp alignment).

   • Ensures all health data—whether from a hospital or a smartwatch—flows into one coherent medical record for AI analysis.

2. Omega Health Graph

   • Acts as a central knowledge layer of each user’s health profile—covering conditions, historical vitals, medication schedules, and more.

   • The AI Doctor can query this graph to see a comprehensive patient record.

3. Omega AI Doctor

   • Combines advanced LLM reasoning with medical guidelines (cardiology, endocrinology, mental health protocols, etc.).

   • Actions:

     • Generates personalized care plans (e.g., adjusting exercise for a hypertensive patient).

     • Flags potential emergencies (e.g., critically high blood pressure readings).

     • Integrates clinical best practices (e.g., guidelines for medication dosage changes).

4. User Engagement

   • Omega Voice Calls: Automated or on-demand calls to discuss new health findings.

   • Omega Chat Interface: Text-based interactions for quick Q&A, symptom checks, or daily check-ins.

   • Proactive Notifications: Mobile or email alerts prompting immediate attention (missed medication, abnormal vitals).

5. Compliance & Governance

   • Purpose: Maintain medical-grade auditing and security. Track data access, store logs for HIPAA/CE.

   • Scope: Any AI recommendation, user’s data change, or manual override by a healthcare professional is recorded and can be reviewed for regulatory compliance.

Typical User Journey

1

Step 1: Data Capture

A wearable device detects an elevated heart rate and logs the reading.

2

Step 2: Ingestion & Health Graph

The new reading merges with existing health data (BP history, known conditions) to provide a more comprehensive health profile.

3

Step 3: AI Doctor Assessment

The AI Doctor evaluates the risk (e.g., detects recent high-stress indicators) and suggests a calming activity or a medication check if necessary.

4

Step 4: User Alert

A voice call or push notification explains the concern and provides recommended next steps for the user.

5

Step 5: Governance & Compliance

All interactions—data updates, AI suggestions, voice call logs—are stored in the compliance layer for audits or potential medical handoffs.

In essence, OmegaX merges clinical best practices with modern AI to give each user an on-demand “doctor in your pocket.” Data from traditional EHRs, labs, and wearables feed into a unified health graph, enabling the Omega AI Doctor to craft context-aware interventions—delivered via human-like voice calls or quick chat, all while respecting stringent medical regulations.

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4. Dive Deeper

Data Feed

AI Doctors

Health Graph

These pages dive deeper into each major aspect of the OmegaX backend, covering ingestion pipelines, AI logic and data relationships.