From Lab to Clinic, KAUST & AmplifAI Partner to Revolutionize Diabetic Care 

Riyadh: King Abdullah University of Science and Technology (KAUST) and health tech leader amplifAI Health join forces to combat diabetes with a revolutionary AI-powered early detection method. Combining KAUST's cutting-edge HyplexTM hyperspectral imaging technology with amplifAI's expertise, the collaboration aims to transform diabetic care. Initially targeting foot complications, this partnership paves the way for earlier diagnosis, improved treatment protocols, and potentially saving millions of lives globally.

KAUST, the leading science and technology university in Saudi Arabia, joins forces with amplifAI health, a local health tech company, to revolutionize early diabetes detection. Their collaboration leverages cutting-edge AI technology with HyplexTM, a revolutionary hyperspectral imaging system developed by KAUST Professor Andrea Fratalocchi.

This powerful partnership initially targets diabetic foot complications, a major concern for millions. A clinical trial is already in the works to validate the new method's effectiveness. The memorandum of understanding underscores KAUST's Smart Health Initiative commitment to improving healthcare, aiming for earlier diagnoses, better treatment plans, and ultimately, fewer amputations.

This marks a significant milestone for KAUST technology, venturing into direct patient care for the first time. The potential impact is immense: saving billions in healthcare costs globally, preventing 1.5 million diabetic foot amputations annually, and ultimately, improving the lives of countless individuals.
HyplexTM's ability to capture terabytes of data per second, far surpassing commercial cameras, unlocks a wealth of information for precise disease detection, as highlighted by KAUST's Vice President for Research and Director of the Smart Health Initiative, Pierre Magistretti. He emphasizes the initiative's focus on enhancing AI's predictive capabilities using KAUST-developed technology, leading to more accurate and efficient diagnoses.