Binghamton University researchers earned SUNY funds to develop AI-powered cancer diagnostics using standard pathology imaging.
Key Details
- 1Binghamton researchers Nancy Guo and John Fetse received SUNY Technology Accelerator Fund grants.
- 2Guo's ClinSegAI project applies AI to identify biomarkers in standard pathology imaging, aiming to speed cancer treatment decisions.
- 3Their model intends to integrate molecular biology data to identify early tumor progression—potentially ahead of conventional radiology findings.
- 4The overall SUNY TAF program awarded $400,000 across five universities for technology commercialization research.
Why It Matters
AI-based analysis of pathology and radiology images could significantly improve early cancer detection and streamline treatment decision-making. This state funding supports translation of academic research toward clinical and commercial impact in cancer diagnostics.
Source
EurekAlert
Related News
•EurekAlert
AI Enhancement Boosts Handheld Ultrasound for Carotid Plaque Detection
AI-powered post-processing improves handheld ultrasound detection of small or faint carotid plaques in community screening.
•EurekAlert
AI Achieves Precision in Generating Radar Images at Specific Attitudes
Researchers introduce a ControlNet-based AI method for precise, attitude-controllable radar image generation of noncooperative targets.
•EurekAlert
RADAR AI Sets New Standard in Abdominal CT Diagnosis
The RADAR vision-language AI model shows expert-level diagnostic ability for abdominal CT across multiple diseases and clinical settings.