Improving risk assessment for uncertain lung nodules using advanced AI techniques
Risk stratifying indeterminate pulmonary nodules with jointly learned features from longitudinal radiologic and clinical big data
This study is looking to improve how doctors determine the risk of certain lung nodules by using information from multiple CT scans and patient records, with the help of artificial intelligence, to give patients a clearer idea of whether their nodules are more likely to be harmless or serious.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Vanderbilt University NIH-funded |
| Lab location | 1 site (Nashville, UNITED STATES) |
| Project ID | NIH-10871696 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy of risk assessment for indeterminate pulmonary nodules (IPNs) by integrating data from repeated CT scans and clinical records. By employing artificial intelligence, the study aims to develop a predictive model that can classify these nodules into low and high malignancy risk categories. This approach seeks to provide a more personalized assessment for patients, potentially leading to better management decisions and outcomes. The methodology involves analyzing dynamic changes in nodules alongside clinical factors such as smoking history and lab results.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals who have been identified with indeterminate pulmonary nodules and require further evaluation to determine their malignancy risk.
Not a fit: Patients with clearly defined 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 and personalized risk assessments for patients with lung nodules, improving clinical decision-making and potentially reducing unnecessary procedures.
How similar studies have performed: Previous research has shown promise in using AI for medical imaging and risk stratification, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
Nashville, UNITED STATES
- Vanderbilt University — Nashville, United States (Active)
Researchers
- Principal investigator: Li, Thomas Zhihe — Vanderbilt University
- Study coordinator: Li, Thomas Zhihe
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.