Using deep learning to analyze cancer treatment effectiveness
Cancer Emulation Analysis with Deep Neural Network
This study is exploring a new way to understand how well cancer treatments work by using advanced computer technology to analyze real-life medical data, which could help improve treatment options for older adults with cancer.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-10725293 on NIH RePORTER |
What this research studies
This research aims to improve how we evaluate the effectiveness of cancer treatments by using advanced deep neural network techniques. Instead of relying solely on traditional randomized clinical trials, which can be difficult to conduct, the study will utilize large amounts of observational data from electronic medical records and insurance claims. By developing new software that employs deep learning, the researchers hope to create more accurate and interpretable models that can provide insights similar to those obtained from clinical trials. This approach could lead to better understanding and treatment options for various cancers, particularly in older adults.
Who could benefit from this research
Good fit: Ideal candidates for this research are older adults diagnosed with various types of cancer, including non-small cell lung cancer.
Not a fit: Patients with early-stage cancers or those not receiving treatment may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective cancer treatments tailored to individual patients, especially among the elderly.
How similar studies have performed: Previous research has shown success in using deep learning for emulation analysis in other complex diseases, indicating a promising approach for cancer treatment evaluation.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Ma, Shuangge — Yale University
- Study coordinator: Ma, Shuangge
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.