Johns Hopkins Grants Aim to Support AI Solutions for Older Patients

With a total slightly exceeding $1 million, a funding round from the Johns Hopkins Artificial Intelligence and Technology Collaboratory for Aging Research (JH AITC) provided several projects with support to propel efforts to develop and use AI to promote the health of older patients.

JH AITC launched in 2021 after receiving $20 million in funding from the National Institute on Aging. Since then, it has established itself as a center for innovation for aging and collaboration among the Johns Hopkins community.

Earlier in 2023, JH AITC provided 14 pilot projects with $3 million. The goal behind this was to excel in research surrounding the application of AI in research practices.

The second funding round focuses on extending funding to create AI-based devices and innovation surrounding aging studies. Specifically, recipients are researching how to use AI to treat cognitive decline.

"At the intersection of technology and geriatrics, we are pioneering a future where artificial intelligence brings resilience and autonomy back into the lives of older adults. The projects we support are more than just advances in health care: They are our commitment to nurturing a society where aging is associated with opportunities for growth, not decline," said Peter Abadir, MD, an associate professor of medicine and co-principal investigator of the JH AITC, in a press release. "We are investing in a future that empowers our seniors."

One grant recipient is a project at the Johns Hopkins School of Medicine. Led by Tracy Vannorsdall, PhD, an associate professor in the Department of Psychiatry and Behavior Sciences and the Department of Neurology at Johns Hopkins School of Medicine, the project aims to use a mobile application and machine learning to predict COVID-19-related outcomes surrounding cognitive decline. According to Vannorsdall, the coronavirus disease is associated with a higher risk of Alzheimer’s disease among older patients.

Led by Vijaya Kolachalama, PhD, an associate professor of medicine at Boston University, another grant recipient team is using speech recording and neuroimaging from the Framingham Heart Study to create deep-learning models for the assessment of Alzheimer's Disease-Related Dementias (ADRD).

The third grant-winning project, led by Kunal Mankodiya, PhD, founder of EchoWear LLC and director of the Wearable Biosensing Lab at the University of Rhode Island, involves an AI-based assessment of cognitive changes.

John A. Batsis, MD, an associate professor of medicine at the University of North Carolina at Chapel Hill School of Medicine, is leading a team in developing a Geriatric Functional Assessment System (GFAS). This tool will allow researchers to evaluate physical function based on visual- and motion-related data gathered by a wearable device.

Finally, a team led by Linda Denney, PhD, assistant professor of public health and community medicine at Tufts University School of Medicine, will use the grant funds to support a project that leverages an insole solution to monitor the extent to which patients fall.

Numerous prior efforts have consisted of using AI to support care for older patients.

In October 2022, researchers from Houston Methodist created an AI model to predict hospitalization outcomes among patients with dementia. They developed the model using thousands of patient encounters, defining risk factors related to demographics, complications, and pre-and post-admission data.

Researchers then reviewed risk factors associated with each type of dementia and used this information to create the AI model. They found that the model achieved an accuracy of 95.6 percent and displayed a stronger performance than other dementia risk assessment methods.