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University team working on smartphone-based technology that could help doctors diagnose health conditions

Electrical & Biomedical Engineering Associate Professor Xiaoshan Zhu receives NSF grant for project

Five people standing in a row in front of trees.

David AuCoin, Jeongwon Park, Xiaoshan Zhu, Hao Xu and Leping Liu are investigating a possible new health sensor that would combine fluorescence technology with AI.

University team working on smartphone-based technology that could help doctors diagnose health conditions

Electrical & Biomedical Engineering Associate Professor Xiaoshan Zhu receives NSF grant for project

David AuCoin, Jeongwon Park, Xiaoshan Zhu, Hao Xu and Leping Liu are investigating a possible new health sensor that would combine fluorescence technology with AI.

Five people standing in a row in front of trees.

David AuCoin, Jeongwon Park, Xiaoshan Zhu, Hao Xu and Leping Liu are investigating a possible new health sensor that would combine fluorescence technology with AI.

A patient waits in an examination room. The doctor enters and the patient explains they aren’t feeling well. The doctor removes a small device from a drawer, scans it over the patient, reads the results on the device and prescribes the patient some medicine.

Sounds like something from a science fiction show, doesn’t it? Well, the future may be closer than you realize. 

Electrical & Biomedical Engineering (EBME) Associate Professor Xiaoshan Zhu and team are looking to turn science fiction into science reality — and the National Science Foundation (NSF) is on board.

“Real sample testing using point-of-care sensors has been challenging because many interfering molecules can degrade the sensor sensitivity,” Zhu said. “In the past years, we developed a fluorescence technology that can pick up weak signals from complex samples with high autofluorescence (background)."

“We have been wondering whether this technology, coupled with AI, can achieve broader applications in practice,” he continued. “NSF’s Convergence Accelerator Program offered us a chance to investigate its potential applications and gain its societal impact.”

Zhu and team have received a $650,000 grant from the NSF to develop a portable smartphone-based platform that uses nanocrystals and artificial intelligence (AI) to help doctors efficiently diagnose conditions in the field.

Zhu and his colleagues — Jeongwon Park and Hao Xu, both EBME associate professors; Microbiology & Immunology Professor David AuCoin; and Quantitative Methods & Learning Sciences Professor Leping Liu — will be collaborating with other academics as well as national laboratories, private companies and the University’s College of Business to create a low-cost, highly accurate system that will be able to detect infectious pathogens, analyze food quality and even detect cancer markers.

The grant, “Smartphone Time-Resolved Luminescence Imaging and Detection (STRIDE) for Point-of-Care Diagnostics,” is part of the NSF’s Convergence Accelerator — a program that “funds teams to solve societal challenges through convergence research and innovation. To enhance its impact, the Accelerator also places teams together in cohorts, synergizing their work through facilitated collaboration,” according to NSF’s website.

This grant marks the first time a school in ΒιΆΉΣ³»­ has been awarded a Convergence Accelerator grant.

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