Understanding the different types of Alzheimer's Disease using clinical data
Leveraging Clinical Data for Phenotyping and Predictive Modelling of Alzheimer’s Disease
This study is looking at how different factors, like genetics and gender, affect Alzheimer's Disease and its progression, using patient records to help create better ways to understand and predict the disease for those living with it.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-10868525 on NIH RePORTER |
What this research studies
This research investigates the complexities of Alzheimer's Disease (AD) by analyzing clinical data to identify various molecular and phenotypic features that influence disease risk and progression. By utilizing advanced machine learning techniques and integrative knowledge networks, the study aims to uncover how different factors, including sex and genetic markers, contribute to the heterogeneity of AD. Patients' electronic medical records will be leveraged to develop predictive models that can help identify specific clinical and molecular characteristics associated with different AD subtypes. This approach seeks to provide a more comprehensive understanding of the disease and improve patient outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with Alzheimer's Disease or those at risk for developing the condition.
Not a fit: Patients with other forms of dementia unrelated to Alzheimer's Disease may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more personalized treatment strategies for Alzheimer's Disease, enhancing patient care and outcomes.
How similar studies have performed: Previous research has shown promise in using integrative approaches to understand Alzheimer's Disease, indicating that this methodology could yield valuable insights.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Tang, Alice Summer — University of California, San Francisco
- Study coordinator: Tang, Alice Summer
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 below.