Using advanced technology to better identify cancerous lung nodules
Classifying malignant pulmonary nodules using biophysics-enhanced artificial intelligence
This study is working on a new way to better spot harmful lung nodules that could mean cancer, using advanced computer models to help doctors make more accurate diagnoses, which could lead to better treatment options for patients.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Boston University (Charles River Campus) NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project ID | NIH-10195872 on NIH RePORTER |
What this research studies
This research aims to improve the accuracy of identifying malignant pulmonary nodules, which are small growths in the lungs that can indicate cancer. By integrating biophysics-based computational models with existing artificial intelligence methods, the study seeks to enhance the predictive power of current classification systems. This approach focuses on understanding the physical environment of tumors, which can significantly influence their behavior and growth. Patients may benefit from more accurate diagnoses, leading to better treatment decisions and potentially improved outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals with pulmonary nodules that require classification to determine the risk of malignancy.
Not a fit: Patients with benign nodules or those who do not have pulmonary nodules may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnoses of lung cancer, reducing unnecessary procedures and improving patient outcomes.
How similar studies have performed: Previous studies have shown promise in using biophysics and artificial intelligence for cancer classification, indicating that this approach could be a significant advancement in the field.
Where this research is happening
Boston, United States
- Boston University (Charles River Campus) — Boston, United States (Active)
Researchers
- Principal investigator: Nia, Hadi Tavakoli — Boston University (Charles River Campus)
- Study coordinator: Nia, Hadi Tavakoli
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.