API Documentation

Complete guide to integrating MedicalAITech into your healthcare applications

Overview

MedicalAITech provides a comprehensive REST API that enables healthcare applications to integrate advanced AI capabilities including medical diagnostics, image analysis, and intelligent chatbots.

HIPAA Compliant

Full compliance with healthcare privacy regulations

Real-time Processing

Lightning-fast responses for critical decisions

Getting Started

To begin using the MedicalAITech API, you'll need to sign up for an account and obtain your API key.

  1. Sign up for a MedicalAITech developer account
  2. Generate your API key from the dashboard
  3. Make your first API request
  4. Explore our comprehensive documentation

Base URL: https://medicalaitech.com/v1

Authentication

All API requests require authentication using your API key in the Authorization header.

Authentication Header 
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

API Endpoints

POST /diagnose

Analyze symptoms and provide diagnostic suggestions based on AI analysis.

Parameters:

  • symptoms (array) - List of symptoms
  • patient_age (integer) - Patient's age
  • patient_gender (string) - Patient's gender
POST /analyze-image

Analyze medical images using computer vision AI.

Parameters:

  • image (file) - Medical image file
  • analysis_type (string) - Type of analysis (xray_chest, mri_brain, etc.)
POST /chat

Interactive AI medical assistant for healthcare consultations.

Parameters:

  • message (string) - User's message or question
  • context (string) - Conversation context
  • session_id (string) - Unique session identifier

Code Examples

Basic Diagnosis Request

JavaScript 
const response = await fetch('https://medicalaitech.com/v1/diagnose', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    symptoms: ['headache', 'fever', 'fatigue'],
    patient_age: 35,
    patient_gender: 'male'
  })
});

const result = await response.json();
console.log(result);

Image Analysis Request

JavaScript 
const formData = new FormData();
formData.append('image', imageFile);
formData.append('analysis_type', 'xray_chest');

const response = await fetch('https://medicalaitech.com/v1/analyze-image', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
  },
  body: formData
});

const analysis = await response.json();

AI Chat Request

JavaScript 
const chatResponse = await fetch('https://medicalaitech.com/v1/chat', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    message: "Patient experiencing chest pain and shortness of breath",
    context: "emergency_triage",
    session_id: "unique_session_id"
  })
});

const aiResponse = await chatResponse.json();

Use Cases

Emergency Triage

AI-powered triage systems that prioritize patients based on symptom severity and urgency.

Radiology Assistance

Computer vision analysis of X-rays, CT scans, and MRIs to assist radiologists.

Clinical Decision Support

AI recommendations for treatment plans and diagnostic pathways.

Patient Monitoring

Continuous AI analysis of patient vitals and early warning systems.

Integration Guide

Follow these steps to integrate MedicalAITech into your healthcare application:

1

Setup Authentication

Configure your API key and set up secure authentication headers.

2

Choose Endpoints

Select the appropriate API endpoints based on your use case requirements.

3

Handle Responses

Implement proper error handling and response processing for your application.

4

Test & Deploy

Thoroughly test your integration and deploy to production environment.

Need Help?

Our support team is here to help you integrate MedicalAITech successfully.

Contact Support