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MIT and Kookmin University Unveil FlowER: A Generative AI Revolutionizing Chemical Reaction Prediction with Physical Constraints
TLDR: Researchers from MIT and Kookmin University have developed FlowER, a novel generative AI system that significantly improves the prediction of chemical reactions by...
Research & Development
Advancing Cancer Diagnosis: YOLOv12 for Automated Mitotic Figure Detection
TLDR: This research paper introduces a robust single-stage mitotic figure detection method using the YOLOv12 object detection architecture. Developed for the MIDOG 2025 challenge,...
Research & Development
Unlocking Influential Nodes in Networks with Unsupervised Learning
TLDR: ReCC is a novel unsupervised deep learning framework for identifying influential nodes in complex networks. It addresses the limitation of supervised methods by...
Research & Development
AI’s Biosecurity Blind Spot: Why Current Defenses Fall Short Against Engineered Threats
TLDR: A new research paper reveals that current AI-powered biosafety tools, such as AlphaFold 3 and other protein-protein interaction predictors, are inadequate for detecting...
Research & Development
Enhancing Mitosis Detection in Digital Pathology with a Hybrid AI Approach
TLDR: Researchers have developed a two-stage AI framework for highly accurate mitosis detection in whole-slide images. The system first uses an improved YOLO11x model...
Research & Development
SDF-YOLO: A Focused AI Approach for Robust Mitotic Figure Detection in Pathology
TLDR: SDF-YOLO is a new, lightweight AI framework based on YOLOv11, specifically designed for robust and efficient detection of small, rare mitotic figures in...