Skip to main navigation Skip to search Skip to main content

I-Corps: Translation potential of using artificial intelligence (AI) to diagnose Alzheimer’s disease and other dementia-related disorders

Project: Research

Abstract & Details

Description

Award ID: 2425827

The broader impact of this I-Corps project is the development of a technology for non-invasive assessment and monitoring of neurocognitive disorders, especially Alzheimers disease. The prevalence of Alzheimers is set to surge, potentially overwhelming current healthcare practices, due to increasing life expectancy and the static number of neurology practitioners. Current diagnoses are largely based on clinical interviews and questionnaires, which are subjective and can lead to recalls and interviewer biases. This technology is a non-invasive technique to screen patients with Alzheimers disease or other dementia-inducing neurocognitive disorders. These tools are designed to help physicians and clinicians rapidly diagnose patients. The technology may improve patient outcomes, enhance the quality of healthcare delivery, improve patient and family comfort, and reduce financial burdens. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of sensor-based artificial intelligence (AI) to analyze speech patterns that can be used to identify early signs of cognitive decline. Integrated into an easily accessible web platform, one model identifies speech pattern differences to assess dementia risk, providing a probability metric. The other model automates the AD8 Dementia Screening scoring, a screening test used to detect early cognitive changes, enhancing efficiency in diagnosis. Both models, utilizing deep learning and natural language processing methods. Preliminary validations affirm the models' accuracy, with full real-world testing underway to ensure reliability. By guiding physicians in the diagnosis and treatment planning process, this technology may facilitate timely and effective medical interventions to streamline dementia detection. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman
StatusClosed
Effective start/end date06/15/2405/31/26

Funding

  • I-Corps Teams: $50,000.00

Active Fiscal Year

  • FY2024
  • FY2026
  • FY2025

Start Fiscal Year

  • FY2024

TIP Programs

  • I-Corps Teams

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 100%)
  • Biotechnology
  • (confidence score: 91%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 100%)
  • Machine Learning (ML)
  • (confidence score: 100%)
  • Artificial Intelligence (excluding ML)
  • (confidence score: 100%)
  • Biotechnology (Broad)
  • (confidence score: 100%)

Congressional District at Award

  • District n. 15 of Pennsylvania

Current Congressional District

  • District n. 15 of Pennsylvania

United States

  • Pennsylvania

Core Based Statistical Area (CBSA)

  • State College, PA

County

  • County: Centre, PA

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine