Snapshot is a web-based cognitive assessment platform designed to detect early signs of dementia by administering two key tests: the Processing Speed Test and the Visual Memory Test. These assessments provide clinicians with insights into a patient’s cognitive health and help determine whether further screening is necessary.
The platform was developed with machine learning enhancements that allow for real-time analysis, improving the patient experience by reducing the test duration when possible. It seamlessly integrates with electronic medical records (EMRs), enabling doctors to schedule tests remotely and allowing patients to complete assessments from their computer, tablet, or phone.
Processing Speed Test
I designed and developed a digital adaptation of the Symbol Digit Modalities Test (SDMT), a widely used assessment for processing speed and cognitive function. I integrated machine learning models trained on existing patient data to predict the final score as early as possible in the test-taking process. When confidence in the prediction was high, the test would end early, reducing patient burden while maintaining accuracy.
Visual Memory Test
I created a test where patients are shown a grid of symbols to memorize and then asked to reconstruct the grid from memory. I implemented dynamic scoring algorithms to assess recall accuracy and identify cognitive impairments.
Impact & Results
I improved patient experience by minimizing test duration without compromising accuracy. I enabled early detection of cognitive decline, supporting proactive intervention. I streamlined clinical workflows with EMR scheduling and remote test administration. I facilitated large-scale screenings by allowing tests to be taken at home, reducing the need for in-person visits.
