Scanbase provides an API that utilizes advanced image processing and machine learning to analyze photographs of rapid diagnostic tests, delivering immediate results to medical companies. This technology addresses the need for timely and accurate diagnostics in healthcare, enhancing patient monitoring and early disease detection.
Funding
$500K 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.
- Startup funding source · Source unavailable
- Startup funding source · Source unavailable
- Startup funding source · Source unavailable
- Startup funding source · Source unavailable
Founders
Product
Problem
Medical companies need a way to quickly and accurately analyze rapid diagnostic tests, but current methods often lack the speed and precision required for timely patient monitoring and early disease detection. Traditional analysis can be subjective and prone to human error, leading to inconsistent results.
Solution
Scanbase provides an API that leverages image processing and machine learning to analyze photographs of rapid diagnostic tests, delivering immediate, objective results. The platform supports patient monitoring by accurately collecting data and alerting healthcare providers to critical changes. Scanbase's AI models can also analyze diagnostic test results, X-rays, MRIs, and CT scans, aiding in the early detection of diseases and abnormalities. The platform transforms unstructured data into usable structured formats, enabling organizations to make data-driven decisions and automate processes.
Target Audience
Scanbase primarily serves medical diagnostic enterprises, healthcare organizations, and healthcare systems seeking to enhance operational efficiency and improve patient outcomes through AI-powered solutions.
Features
- API for analyzing photographs of rapid diagnostic tests
- Computer vision for patient monitoring and early disease detection
- Predictive AI models and LLMs to surface early disease indicators from historical lab results
- NLP and machine learning techniques to extract information from unstructured data
- Image pipelines with robust image processing
- GPU and cloud integration for scalability
- Data privacy and security adhering to GDPR or HIPAA