Penn State awarded $1.2M grant for Alzheimer’s detection study

A team of Penn State University researchers has been awarded a $1.2 million grant from the NIH to develop a machine learning system for the early detection of Alzheimer’s disease.

Alzheimer’s disease affects nearly 6 million Americans, and is the most common form of dementia, according to the CDC.

According to a release from the university, the detection system will provide a minimally invasive approach for identifying Alzheimer’s disease. Early detection will allow clinicians to give timelier treatments and interventions for patients with AD.

Currently, collecting data that provides information on biomarkers for detection of AD is expensive and time consuming, Fenglong Ma, PhD, assistant professor of information sciences and technology at Penn State, said in the release.

“Our team wants to contribute to a solution to these issues by developing a novel and minimally-invasive system,” Ma said in the release. “By integrating a multimodal biosensing platform and a machine learning framework, we expect the system to improve early detection of AD and enhance AD detection accuracy.”

According to Sharon Huang, PhD, professor of information sciences and technology at Penn State, the research team plans to design a system that utilizes a variety of biosensors, including optical, mechanical and electrochemical nano-sensors, that will analyze biological samples.

“Given different types of sensing data, for instance, data acquired from different biochemical markers in human body fluids, machine learning can perform feature selection and establish associations between an individual biomarker and Alzheimer's disease, or between a set of biomarkers and the disease,” Huang said in the release.