Solution

The use of photonic sensors and artificial intelligence (AI) for urosepsis diagnosis from urine samples is an area of active research. Photonic sensors use light to detect changes in the composition of a sample, which can provide valuable information about the presence of bacterial infections.

Our solution have investigated the use of photonic sensor in combination with AI algorithms for urosepsis diagnosis from urine samples. Our solution is photonic sensor-based platform for the rapid and sensitive detection of bacterial infections in urine samples. The platform used AI algorithms to analyze the sensor data and provide accurate and fast diagnosis of urosepsis. The use of photonic sensors and AI algorithms for urosepsis diagnosis from urine samples is a promising area of research that may lead to faster and more accurate diagnosis of this serious condition. However, more research is needed to fully validate the accuracy and effectiveness of these approaches in clinical settings.

Brief description of our device:

• equipped with optoelectronic sensor based on optical fiber technology
• Optoelectronic sensor capable to detect E. coli leading to urosepsis
• Multiple use, fast result < 20 min
• Green Technology - we do not use any chemical during the measurements, only patients urine sample
• TRL 5
• Competitive advantages with respect to known and applied methods and reduced environmental impact
• Multiple use probe (Current methods: one time use only)
• Result in less than 20 min (Current methods: 6h to 48h)
• Each measurement < 1$ (Current methods: 5-100$)

Possibilities of market application:

• Hospitals (Emergency Units)
• Point of Care Testing
• Possibility to adapt to other diseases
• Possibility to adapt to detect different biomarkers (cardiology, oncology, pain…)