Documentation

Everything you need to integrate AfriBiobank AI tools into your applications

Quick Start

Get up and running in minutes

API Reference

Complete API documentation

Authentication

Secure your API requests

SDKs

Client libraries for all languages

Getting Started

Installation

Install the AfriBiobank SDK using your preferred package manager:

# Python
pip install afribiobank

# Node.js
npm install @afribiobank/sdk

# R
install.packages("afribiobank")

First API Call

Make your first API call to analyze a medical image:

import afribiobank

# Initialize the client
client = afribiobank.Client(api_key="your_api_key")

# Analyze a chest X-ray
result = client.chest_analysis.predict(
    image_path="chest_xray.jpg",
    model="tb-detection-v2"
)

print(result.predictions)

Authentication

All API requests require authentication using an API key. Include your API key in the request header:

Authorization: Bearer YOUR_API_KEY

Keep your API key secure

Never expose your API key in client-side code or public repositories. Store it securely in environment variables.

API Reference

POST/api/v1/brain-analysis

Neuroimaging

Analyze brain MRI scans for tumor detection and segmentation

POST/api/v1/chest-analysis

Radiology

Detect TB, pneumonia, and thoracic pathologies from chest X-rays

POST/api/v1/skin-analysis

Dermatology

Classify skin lesions and detect melanoma

POST/api/v1/retinal-analysis

Ophthalmology

Grade diabetic retinopathy and detect retinal diseases

POST/api/v1/segmentation

Image Processing

Segment organs and anatomical structures

Official SDKs

Python

JavaScript/TypeScript

R

Java

Coming Soon

Additional Resources

Tutorials

Step-by-step guides for common use cases

Browse Tutorials

Code Examples

Ready-to-use code snippets and samples

Research Papers

Scientific publications and methodology

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