ZemedicAI

ZemedicAI offers an AI-powered platform for medical imaging analysis, enhancing diagnostic accuracy for healthcare providers in Africa. The solution analyzes X-rays, skin lesions, and ultrasounds, providing detailed insights to support clinical decisions, even in resource-limited settings.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Healthcare providers in Africa face challenges in accessing advanced medical imaging analysis, particularly in resource-limited or remote areas. This limits the early detection and accurate diagnosis of critical conditions such as pneumonia, tuberculosis, and melanoma, impacting patient outcomes.

Solution

ZemedicAI provides an AI-powered medical imaging analysis platform designed to enhance diagnostic accuracy and efficiency for healthcare providers across Africa. Our solution leverages deep learning models trained on extensive African datasets to analyze various medical images, including X-rays, skin lesions, and ultrasounds. The platform offers detailed diagnostic insights, including abnormality detection and confidence scoring, to support clinical decision-making. Flexible deployment options, such as solar-powered booths and SDK integration, ensure accessibility even in environments with limited infrastructure.

Target Audience

The primary customers are healthcare providers, including hospitals, clinics, and diagnostic centers across Africa, particularly those operating in underserved or remote regions.

Features

AI-powered analysis for Chest X-rays, Skin Lesions, and Ultrasound images.
Deep learning models with over 1 million chest X-rays and 500,000 ultrasound images in training data.
Detection of up to 14 conditions in Chest X-rays, including pneumonia, tuberculosis, and pleural effusion.
Detection of critical findings in brain ultrasounds, such as intracranial hemorrhage and mass effect, with 92% average accuracy.
Skin lesion analysis achieving 97% accuracy for melanoma and other skin conditions.
Heatmap visualizations highlighting regions of interest with color-coded confidence levels.
Explainable AI features that indicate specific features influencing diagnostic predictions.
Deployment options include solar-powered, self-contained diagnostic booths for remote areas.
SDK integration for seamless incorporation into existing PACS and medical imaging software.
On-premise processing option for enhanced data privacy and compliance.