Using advanced AI to predict melanoma recurrence by analyzing imaging and genetic data.
Official title: Explainable Artificial Intelligence for Melanoma Recurrence Prediction via Integrative Modeling of Multiplexed Imaging with Transcriptomics and Histopathology
Funded at Massachusetts General Hospital · NIH-11032046 · Data updated 2026-11-12
This study is looking to help people with early-stage melanoma by using advanced imaging and genetic information to better predict if their cancer might come back, so they can receive more personalized care and monitoring based on their specific risk.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts General Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | February 9, 2024 |
| Project end | January 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $176,040 |
| NIH project number | 5K99CA286966-02 |
| Project ID | NIH-11032046 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with early-stage (stage I/II) melanoma.
✕Less likely to help
Patients with advanced-stage melanoma or those who have already experienced recurrence may not benefit from this research.
What this research studies
This research aims to improve the prediction of melanoma recurrence in patients with early-stage melanoma by integrating advanced imaging techniques and genetic information. By utilizing multiplexed tissue imaging and spatial transcriptomics, the study will analyze the interactions and characteristics of cells in the melanoma microenvironment. The goal is to develop machine-learning models that can accurately identify patients at high risk for recurrence, enabling personalized treatment and better surveillance strategies. Patients may benefit from more tailored monitoring and interventions based on their individual risk profiles.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of melanoma recurrence, allowing for personalized treatment plans and improved patient outcomes.
How similar studies have gone: Previous research has shown promise in using AI and multi-modal data to improve cancer prognostics, indicating a potential for success in this novel approach.
Where this research is happening
-
Massachusetts General Hospital
Boston, United States Active
Researchers
- Principal investigator: Wan, Guihong — Massachusetts General Hospital
- Study coordinator: Wan, Guihong
Related research
Other NIH-funded projects on the same topics.
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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.