Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in large radiographic collections. By automatically verifying body-part, ...
This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...
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Deep learning model dramatically improves subgraph matching accuracy by eliminating noise
A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the accuracy of subgraph matching—a critical task in fields ranging from drug ...
Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...
An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results ...
New study presented at HRX Live 2025 demonstrates continued advancement of company’s AI program HeartBeam's AI algorithm performed equally well on HeartBeam 3D ECG system and standard 12L ECGs in ...
Understanding how cities grow is vital for shaping sustainable urban futures—but mapping the true extent of urban expansion remains a formidable technical hurdle. A new global study takes on this ...
While deep learning models deliver exceptional precision, they come at a cost. SAM offers a practical balance between ease of use and accuracy. Understanding these trade-offs is key to designing ...
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