Using AI to improve cancer diagnosis through better explanations
SCH: Counterfactual Explanations for AI-Assisted Cancer Diagnosis and Subtypiing
This study is working on making cancer diagnoses more accurate by using smart computer models that can explain their predictions about tissue samples, helping doctors understand why a tumor might be considered aggressive or not, so they can make better treatment choices.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers, the State Univ of N.j. NIH-funded |
| Lab location | 1 site (Piscataway, United States) |
| Project ID | NIH-11060758 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy of cancer diagnoses by developing AI models that can explain their predictions for histopathological images. It aims to create a framework that uses counterfactual explanations, allowing pathologists to understand how different features in tissue samples could influence the diagnosis of tumors. By generating explanations that clarify why a model predicts a tumor as aggressive or non-aggressive, the project seeks to improve the interpretability of AI tools in clinical settings. This could lead to more informed treatment decisions based on AI-assisted evaluations.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients diagnosed with head and neck squamous cell carcinoma (HNSCC) who are undergoing histopathological evaluation.
Not a fit: Patients with cancers that are not related to head and neck squamous cell carcinoma may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and interpretable cancer diagnoses, ultimately improving patient outcomes.
How similar studies have performed: Other research has shown promise in using AI for medical imaging, but the specific approach of counterfactual explanations in histopathology is relatively novel.
Where this research is happening
Piscataway, United States
- Rutgers, the State Univ of N.j. — Piscataway, United States (Active)
Researchers
- Principal investigator: Wang, Hao — Rutgers, the State Univ of N.j.
- Study coordinator: Wang, Hao
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.