Adaptive machine learning platform for image-based rapid diagnostic test interpretation
This technology is a machine learning platform that automatically interprets rapid diagnostic tests from images and uses self-supervised pre-training to adapt to new test kits with minimal data.
Unmet Need: Automated and accurate interpretation of diverse rapid diagnostic tests
Current point-of-care and at-home rapid diagnostic tests rely on users to visually interpret faint or ambiguous test lines, leading to high error rates, misguided clinical decisions, and inconsistent results. Existing digital interpretation tools typically require large, kit-specific training datasets and fail to generalize to new or updated test formats. As rapid diagnostic kits continue to evolve, there are currently no scalable methods to ensure accurate and standardized interpretation across diverse kit designs.
The Technology: Automated image-based machine learning platform for reliable rapid test interpretation
This technology is an automated image interpretation system for rapid diagnostic tests that uses a neural network pre-trained to recognize key visual features of test kits. In its pre-training stage, the model learns general structural patterns by converting test kit images to grayscale, extracting features such as edges, and reconstructing these simplified images through a feature-extraction and decoding process. By minimizing reconstructions during training, the system refines its feature extractor to capture line-based patterns and other consistent visual characteristics across different test kit designs. This structure enables the model to adapt efficiently to new rapid test kits with limited data. This technology can be implemented on a smartphone, providing accurate interpretation in a portable, user-accessible format.
This technology has been validated using a large dataset that spans multiple rapid test kits.
Applications:
- Automated interpretation of point-of-care and at-home rapid diagnostic tests
- Smartphone-based reader for lateral flow assays across healthcare and consumer settings
- Clinical decision-support tool for standardized test interpretation
- Quality control and manufacturing support for rapid test kit developers
- Research tool for analysis of rapid test formats
Advantages:
- Provides standardized and automated interpretation of rapid diagnostic tests
- Reduces user-dependent error and misdiagnoses
- Compatible with smartphones
- Reliable across diverse kits
- Scalable and cost-effective
Lead Inventor:
Patent Information:
Patent Pending (US20230274538)
Related Publications:
Tech Ventures Reference:
IR CU21034
Licensing Contact: Dovina Qu