Using deep learning to find signs of cognitive impairment in health records
Official title: A deep learning algorithm to detect signs of cognitive impairment in electronic health records
Funded at Massachusetts General Hospital · NIH-11111272 · Data updated 2026-11-12
This study is working on a smart computer program called Decipher-AI that helps doctors spot signs of memory problems related to Alzheimer's and other dementias by looking at patients' health records, making it easier to catch these issues early and accurately.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts General Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | June 15, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $405,398 |
| NIH project number | 5R01AG082698-02 |
| Project ID | NIH-11111272 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals who have experienced cognitive concerns or are at risk for Alzheimer's disease and related dementias.
✕Less likely to help
Patients without any cognitive concerns or those who do not have access to electronic health records may not benefit from this research.
What this research studies
This research aims to develop a deep learning algorithm called Decipher-AI to improve the detection of cognitive impairment related to Alzheimer's disease and other dementias by analyzing electronic health records (EHR). The algorithm will utilize data from clinical notes, patient health histories, and health system interactions to identify patterns indicative of cognitive decline. By leveraging advanced natural language processing techniques, the study seeks to enhance the accuracy of cognitive impairment diagnoses, which are often missed or misclassified in traditional assessments.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of cognitive impairment, allowing for timely interventions and better management of Alzheimer's disease and related dementias.
How similar studies have gone: Other research has shown promise in using machine learning and deep learning approaches for improving diagnostic accuracy in various medical fields, suggesting potential success for this novel application.
Where this research is happening
-
Massachusetts General Hospital
Boston, United States Active
Researchers
- Principal investigator: Das, Sudeshna — Massachusetts General Hospital
- Study coordinator: Das, Sudeshna
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.