Smartphone-based Technology in Healthcare Diagnostics

A patient is awaiting in an examination room. Upon the doctor’s entrance, the patient articulates their ill-feelings. The doctor retrieves a small device from a drawer, utilizes it to scan the patient, interprets the results, and prescribes the necessary medication.

Are we witnessing the inception of a futuristic television series? Surprisingly, this scenario is not as implausible as it may appear. The Electrical & Biomedical Engineering (EBME) team at the University of Nevada, Reno, under the leadership of Associate Professor Xiaoshan Zhu, is engaged in a pioneering project that has the potential to transform healthcare diagnostics. Their efforts have garnered support from the National Science Foundation (NSF), signaling the significance of their work.

Zhu and his team are diligently working on the creation of a portable smartphone-based platform incorporating nanocrystals and artificial intelligence (AI) to facilitate real-time diagnosis of health conditions by medical professionals. Their ultimate goal is to develop a system capable of identifying infectious pathogens, assessing food quality, and detecting cancer markers at an affordable cost and with exceptional precision.

The NSF has awarded the team a grant of $650,000 for their project, “Smartphone Time-Resolved Luminescence Imaging and Detection (STRIDE) for Point-of-Care Diagnostics,” as part of the NSF’s Convergence Accelerator Program, which is designed to address societal challenges through convergence research and innovation.

Central to the team’s innovation is a fluorescence technology proficient in detecting faint signals amidst high background fluorescence in complex samples. By integrating this technology with AI, they aim to expand its applications and maximize its societal impact. Their objective is to enable point-of-care testing using sensors, bypassing the challenges posed by interfering molecules that can compromise sensor sensitivity.

Zhu and his colleagues, including EBME associate professors Jeongwon Park and Hao Xu, Microbiology & Immunology Professor David AuCoin, and Quantitative Methods & Learning Sciences Professor Leping Liu, will collaborate with academic institutions, national laboratories, private companies, and the University’s College of Business to bring their vision to fruition.

The significance of the grant awarded to the University of Nevada, Reno, for this project cannot be overstated, as it marks the first occasion a school in Nevada has received a Convergence Accelerator grant from the NSF. This acknowledgment underscores the importance and potential impact of the team’s work in advancing healthcare diagnostics.

The development of this smartphone-based technology holds promise for revolutionizing the healthcare industry. It stands to enhance the speed and accuracy of diagnosing various conditions, ultimately elevating patient care and outcomes. With the backing of the NSF and their collaborative partners, Zhu and his team are well-positioned to transform this concept from science fiction into a tangible reality with the potential to benefit countless individuals in the future.