Using machine learning to understand the immune system in patients
Machine Learning for Integrative Modeling of the Immune System in Clinical Settings
This study is looking at how our immune system works by using smart computer programs to better understand immune cells and their interactions, with the goal of helping create new treatments and tests for patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-10883723 on NIH RePORTER |
What this research studies
This research focuses on developing advanced machine learning algorithms to analyze the immune system's responses in clinical settings. By examining immune cells and their interactions at a single-cell level, the study aims to create predictive models that can inform the development of new immune therapies and diagnostic tests. The researchers will utilize large datasets and integrate existing immunological knowledge to enhance the accuracy and reproducibility of their findings. This innovative approach seeks to uncover complex relationships within the immune system that are crucial for improving patient care.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals with immune system disorders or those undergoing treatment that affects their immune response.
Not a fit: Patients with stable immune conditions that do not require intervention may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective immune therapies and diagnostic tools for patients with immune-related conditions.
How similar studies have performed: Previous research has shown promise in using machine learning for analyzing complex biological systems, indicating potential success for this novel approach.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Aghaeepour, Nima — Stanford University
- Study coordinator: Aghaeepour, Nima
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.