Using machine learning to improve biological data analysis and healthcare tools
Machine Learning and Control Principles for Computational Biology
This study is working on new computer tools that use smart technology to better understand biological data, which could lead to improved tests and treatments for patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project ID | NIH-10928788 on NIH RePORTER |
What this research studies
This research focuses on developing advanced machine learning models to enhance the analysis of biological data and improve healthcare diagnostics. By integrating principles from engineering, particularly control systems, the project aims to create more robust and reliable computational tools. The research will explore three main areas: modeling dynamic biological systems, optimizing machine learning processes, and applying control principles to study microbial communities. Patients may benefit from improved diagnostic tools and treatments derived from these advanced models.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals with conditions that can be analyzed through advanced biological data and machine learning techniques.
Not a fit: Patients with conditions that do not involve biological data analysis or machine learning applications may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnostics and innovative treatments in healthcare.
How similar studies have performed: Other research has shown success in using machine learning for biological data analysis, indicating a promising potential for this approach.
Where this research is happening
Boston, United States
- Brigham and Women's Hospital — Boston, United States (Active)
Researchers
- Principal investigator: Gibson, Travis Eli — Brigham and Women's Hospital
- Study coordinator: Gibson, Travis Eli
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.