Deep learning model predicts rice protein interactions from sequence data
A new deep learning framework called RCNNricePPI predicts rice protein-protein interactions from amino acid sequences, achieving an accuracy of 0.8996 ...
A new deep learning framework called RCNNricePPI predicts rice protein-protein interactions from amino acid sequences, achieving an accuracy of 0.8996 ...
A systematic review of 306 studies finds most machine learning crash severity models ignore class imbalance and a large share ...
UniLoopNet predicts enhancer–promoter, enhancer–enhancer, CTCF-mediated, and stripe-associated chromatin interactions from DNA sequence using a multi-task deep learning framework.
Every year, tens of millions of mammograms are performed worldwide, and many of them contain a quiet clue about a ...
A systematic review of 45 studies finds that the most accurate AI models in high-stakes domains are often the least ...
A new review maps how artificial intelligence is transforming mosquito identification, disease forecasting, and vector control worldwide.
A new promptable diffusion-enhanced framework achieved 98.1% classification accuracy and a 93.2% Dice score for explainable brain tumor segmentation and ...
A dual-path attention fusion network combining Swin Transformer and frozen DINOv2 features reached 99.24% accuracy on a leakage-screened hold-out test ...
A published study reports that a Big Bang-Big Crunch optimized Peephole LSTM model classified course records in a 10,000-record dataset ...
A new AI framework combining attention-enhanced YOLOv8 and Bald Eagle Optimization achieved 98.94% accuracy in detecting transmission and distribution faults ...
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© 2026 Scienmag - Science Magazine