AZmed provides the Rayvolve® AI Suite, which utilizes artificial intelligence to enhance the efficiency of medical imaging workflows by reducing reading times and minimizing false negatives. This technology has been clinically validated and deployed in over 2,500 healthcare centers worldwide, significantly improving diagnostic precision and alleviating workload burdens for healthcare professionals.
Funding
$21.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Radiologists face increasing workloads and time constraints in interpreting medical images, leading to potential diagnostic errors and delays in patient care. The complexity of image analysis, particularly in detecting subtle anomalies, can contribute to missed or delayed diagnoses.
Solution
AZmed provides the Rayvolve® AI Suite, a collection of artificial intelligence tools designed to enhance medical imaging workflows and improve diagnostic precision. The AI suite analyzes X-ray images to identify potential fractures and other critical findings, flagging suspicious areas for radiologists' review. By automating initial image screening and highlighting key areas of interest, Rayvolve® reduces reading times and minimizes the risk of false negatives. The platform integrates seamlessly into existing Picture Archiving and Communication Systems (PACS), providing radiologists with AI-powered assistance without disrupting their established workflows.
Target Audience
The primary target audience includes radiologists, emergency room physicians, and other healthcare professionals involved in the interpretation of medical images.
Features
- AI-powered detection of fractures and other anomalies in X-ray images
- Automated image screening to prioritize critical cases and reduce reading times
- Integration with existing PACS systems for seamless workflow integration
- Algorithms validated by clinical research and deployed in healthcare centers worldwide
- Tools for analyzing chest, trauma, and musculoskeletal X-rays
- Algorithms to measure angles and lengths in medical images
- AI-based bone age assessment based on Greulich & Pyle reference methodology (coming soon)