An AI-assisted screening platform within a multivariate framework for biomarkers of mild cognitive impairment due to Alzheimer's disease

PROJECT SUMMARY Accumulating evidence indicates that every 65 seconds, someone develops Alzheimer's disease (AD) in the United States, and over 5.7 million Americans have the condition. Alzheimer's and other dementias will cost the nation $277 Billion by 2050.

The major problem is that many people with cognitive impairment (CI) may not know they have it because dementia is underdiagnosed and underreported.

There is a lack of low-cost and non- invasive screening instruments to identify individuals at risk for CI with high accuracy automatically.

Therefore, considering the global and societal implications of the dementia epidemic, better strategies are needed to identify patients at risk for dementia. An eye health evaluation offers a unique perspective on the health of our eyes and our bodies.

For example, visual observation of the retina as a diagnostic modality is already widely used to detect high blood pressure, diabetes, high cholesterol, and even brain tumors since a physician can see the optic nerve, which is part of the brain. Thus, an eye test may also be a potential solution to detect CI.

While early manifestations of numerous risk factors (e.g., diabetes, hypertension, and heart disease) have been found in the human retina, they may confound the first signs of CI.

In healthcare, the complexity and rise in data volume have contributed to the remarkable worldwide interest of Artificial Intelligence (AI) applications in medicine.

Therefore, we aim to provide a practical near-term risk assessment of CI through AI, by identifying and utilizing novel multivariate biomarkers (including eye markers) with a better discrimination power.

In this Phase I STTR, iScreen 2 Prevent, LLC, the University of Miami, and the iCareHub, LLC, will develop an AI-based screening platform for early detection of CI due to AD.

Our preliminary data show that multivariate eye biomarkers are related to cognitive status and can be used to discriminate mild CI patients from cognitively healthy subjects (age-matched (55+ years old), area under the receiving operating curve (AUROC)=0.90 (SE=0.050), p