
AI-based analysis of tumor pathology slides can predict immunotherapy outcomes in rare cancers, according to a recent MD Anderson study.
Key Details
- 1MD Anderson researchers applied AI to analyze pathology slides from rare cancer patients undergoing immunotherapy.
- 2The AI tool rapidly quantified immune cell infiltration and tumor content using routine pathology slides.
- 3Combined metrics (immune infiltration increase and tumor content decrease) strongly predicted positive immunotherapy response.
- 4Patients with favorable markers had a 64% lower risk of progression or death and nearly quadrupled median survival (42 vs. 10 months).
- 5Study funded by Merck, with AI analysis support from Lunit.
- 6Further validation in larger cohorts is necessary before clinical adoption.
Why It Matters

Source
EurekAlert
Related News

UVA's $4M NIH Grant Backs AI to Optimize Cardiac MRI Therapies
UVA secures $4 million NIH funding to develop GenStrain, an AI model using MRI data to personalize cardiac pacing therapies.

Machine Learning Models Predict Cancer Risk with Routine Health Data
Researchers developed machine learning models using routinely collected health data to predict individual risk for 20 common cancers, outperforming traditional methods for several cancer types.

Duke Receives $25M to Lead National Trustworthy AI Hub for Dementia and Aging
Duke University has launched a $25 million national center to make AI for aging and dementia clinically robust and trustworthy.