M-ISIC: Open-Source Platform to Improve Skin Cancer Detection With Images
Official title: M-ISIC: A Multimodal Open-Source International Skin Imaging Collaboration Informatics Platform for Automated Skin Cancer Detection
Funded at Sloan-Kettering Inst Can Research · NIH-11384583 · Data updated 2026-11-12
A multi-institution effort to build and share an open, AI-powered platform that improves how skin cancer is detected from images.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Sloan-Kettering Inst Can Research NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 1, 2022 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $804,591 |
| NIH project number | 5U24CA264369-05 |
| Project ID | NIH-11384583 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients with skin lesions who would consent to have their images used for education, model development, and validation within de-identified datasets.
✕Less likely to help
Patients whose images are not used for model development or who choose not to participate would not directly benefit from the study.
What this research studies
This project creates an automated, multimodal pipeline to ingest, organize, and curate skin images from diverse devices, with the goal of improving AI systems that detect skin cancer. It builds on the ISIC Archive and Girder platform to provide standardized data and annotations for education and model development. By giving clinicians and researchers access to well-curated datasets, the work aims to support better early detection, including melanoma, through more robust AI tools. The initiative emphasizes data quality, interoperability, and reproducibility to advance clinical skin cancer care.
Why it matters
Potential benefit: If successful, clinicians could rely on more accurate AI-assisted skin cancer screening, potentially catching cancers earlier and improving outcomes.
How similar studies have gone: Prior similar efforts with ISIC data and AI dermatology tools have shown promise, but this project emphasizes standardized, cross-device data integration to advance reliability.
Where this research is happening
-
Sloan-Kettering Inst Can Research
New York, United States Active
Researchers
- Principal investigator: Rotemberg, Veronica Miriam — Sloan-Kettering Inst Can Research
- Study coordinator: Rotemberg, Veronica Miriam
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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.