Researchers developed an electrochemical biosensor and AI system that accurately detects lung cancer from breath samples.
Key Details
- 1University of Texas at Dallas and UT Southwestern developed an electrochemical biosensor for breath analysis.
- 2The technology uses AI to analyze eight volatile organic compounds linked to thoracic cancers.
- 3In a study with 67 patients (30 biopsy-confirmed cancers), the device identified cancer-linked VOCs with 90% accuracy.
- 4The approach is designed for early, noninvasive, and affordable screening of lung and esophageal cancers.
- 5The technology was reported in the August issue of Sensing and Bio-Sensing Research.
Why It Matters
This innovation could enable routine, noninvasive, and cost-effective early detection of lung and other thoracic cancers, potentially improving survival rates and reducing burdens on healthcare systems. The integration of machine learning in biosensing highlights the expanding role of AI in clinical cancer diagnostics.
Source
EurekAlert
Related News
•EurekAlert
Researchers Develop All-Optical Synapse for Neuromorphic Imaging Systems
A new artificial synapse, controlled entirely by light, enables in-sensor neuromorphic processing for more efficient and noise-resistant imaging systems.
•EurekAlert
Mayo Clinic Showcases Imaging AI and Early Cancer Detection Advances at ASCO 2026
Mayo Clinic researchers will present over 30 studies at ASCO 2026, highlighting new advances in imaging AI, data science, and early cancer detection.
•EurekAlert
AI-Simulation Approach Achieves 90% Faster Brain MRI with Minimal Data
A simulation-based AI method can reconstruct brain MRI scans with only 10% of the usual data, greatly reducing scan times.