Project number
25056
Organization
Craig M. Berge Dean's Fund
Offering
ENGR498-F2024-S2025
CKD affects approximately 37 million adults in the United States. Many of these patients also experience abnormal electrolyte levels that can lead to further comorbidities. Hyperkalemia (high potassium) occurs in 40% to 50% of patients. This condition can result in dangerous heart rhythm problems. Additionally,
hyperphosphatemia (high phosphorus) occurs in 70% to 80% of patients and contributes to bone disease and increased cardiovascular risk. Knowing CDK patients’ potassium and phosphorus levels is therefore critical.
The team addressed this need by creating a dual-measurement, AI-based approach to determining food electrolyte content. The system combines image recognition technology for rapid, everyday assessment with physical measurements via “grind and find” for high-accuracy validation. The image recognition system leverages machine learning and web-based information to continuously improve its accuracy in classifying food items and estimating their potassium and phosphate levels. The
grind and find method represents the team’s ongoing research to establish precise measurement standards for potassium and phosphorus in food items. This in turn helps validate and improve the image recognition system’s accuracy.
hyperphosphatemia (high phosphorus) occurs in 70% to 80% of patients and contributes to bone disease and increased cardiovascular risk. Knowing CDK patients’ potassium and phosphorus levels is therefore critical.
The team addressed this need by creating a dual-measurement, AI-based approach to determining food electrolyte content. The system combines image recognition technology for rapid, everyday assessment with physical measurements via “grind and find” for high-accuracy validation. The image recognition system leverages machine learning and web-based information to continuously improve its accuracy in classifying food items and estimating their potassium and phosphate levels. The
grind and find method represents the team’s ongoing research to establish precise measurement standards for potassium and phosphorus in food items. This in turn helps validate and improve the image recognition system’s accuracy.