Spanish researchers introduce RNACOREX, open-source software illuminating hidden genetic networks in cancer and predicting patient survival with transparent AI.
Key Details
- 1RNACOREX detects key microRNA–mRNA regulatory interactions using data from 13 tumor types in TCGA.
- 2The tool matches advanced AI models in survival prediction accuracy, but with interpretable molecular maps.
- 3It is open-source, freely available via GitHub and PyPI, and designed for easy adoption in research labs.
- 4The software enables stratification of patient outcomes and identification of shared/unique molecular patterns across cancers.
- 5Backed by the University of Navarra, it advances explainable AI for precision oncology and ongoing functionality is planned.
Why It Matters
Explainable AI tools like RNACOREX can bridge the gap between opaque prediction models and clinicians' need for biological interpretability—critical for translating multi-omic data into actionable insights in oncology, with potential cross-disciplinary impact for radiology-AI integration.
Source
EurekAlert
Related News
•EurekAlert
AI Accelerates Radiopharmaceuticals, Boosts Personalized Dosimetry in Cancer
Machine learning is driving advancements in radiopharmaceutical drug discovery and optimizing patient-specific dosimetry for precision cancer therapy.
•EurekAlert
Physicians Overly Trust Erroneous AI, Ignore Contradictory Evidence
Physicians tend to trust incorrect AI advice, even when evidence contradicts it, suggesting risks in clinical decision-making with AI tools.
•EurekAlert
Concerns Raised Over Unverified Datasets in AI Health Prediction Models
A new study finds widely used AI health prediction models are built on datasets with unverifiable origins, raising safety and validity concerns.