Using deep learning to predict cancer treatment outcomes
Official title: Integrative Deep Learning Models for Multimodal Markers of Cancer Treatment Outcomes
Funded at Case Western Reserve University · NIH-10988982 · Data updated 2026-11-12
This study is looking to use advanced technology to help doctors understand how different cancer patients might respond to standard chemotherapy, so they can find better treatment options for those who may not benefit from it.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Case Western Reserve University NIH-funded |
| Lab location | 1 site (Cleveland, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $39,869 |
| NIH project number | 1F99CA294169-01 |
| Project ID | NIH-10988982 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include cancer patients who are currently undergoing or are eligible for standard chemotherapy treatments.
✕Less likely to help
Patients who are not undergoing chemotherapy or those with cancers that do not respond to the therapies being investigated may not benefit from this research.
What this research studies
This research aims to develop advanced deep learning models that analyze various types of data, such as imaging and genetic information, to better predict how cancer patients will respond to standard chemotherapy. By identifying patients who are unlikely to benefit from traditional treatments, the study seeks to guide them towards more effective alternative therapies, like targeted agents or immunotherapy. The approach involves integrating multimodal markers to create a comprehensive understanding of each patient's unique cancer profile, which could lead to more personalized treatment plans.
Why it matters
Potential benefit: If successful, this research could significantly improve treatment outcomes for cancer patients by ensuring they receive the most effective therapies tailored to their specific conditions.
How similar studies have gone: Other research has shown promise in using machine learning and deep learning approaches for predicting treatment outcomes in oncology, indicating that this approach has potential for success.
Where this research is happening
-
Case Western Reserve University
Cleveland, United States Active
Researchers
- Principal investigator: Krebs, Olivia — Case Western Reserve University
- Study coordinator: Krebs, Olivia
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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.