AI Pipeline Turns Brain MRI Saliency Maps into Diagnostic Reports
A benchmark study couples CNN saliency maps, a cortical atlas and three LLMs to generate interpretable diagnostic reports from brain ...
A benchmark study couples CNN saliency maps, a cortical atlas and three LLMs to generate interpretable diagnostic reports from brain ...
A comparative study of nine U-Net-based deep learning configurations found U-Net with a VGG16 backbone achieved the best overall lung ...
Geant4 Monte Carlo simulations show that a 5 wt% lead-loaded plastic scintillator produces a measurable 511 keV photopeak with detection ...
A hybrid CNN–transformer model produces 128-dimensional medical image embeddings that stay robust under noise, blur, cropping, and occlusion across four ...
A new zero-watermarking scheme for color medical images uses VGG19 feature extraction, DCT and cyclic chaos encryption to verify copyright ...
A new review in Cardiovascular Ultrasound explains how artificial intelligence tools, including deep learning PISA segmentation and 3D Auto Color ...
A new machine learning framework called CARDINAL improved discrimination and calibration for grading diastolic dysfunction in a small echocardiographic cohort ...
A lightweight dual-branch AI framework called NeuroCST classified Alzheimer's disease stages from MRI scans with 98.42 percent accuracy while using ...
A multi-phase MRI deep learning model combined with clinical predictors differentiated hepatocellular carcinoma from mass-forming intrahepatic cholangiocarcinoma with AUCs of ...
A hybrid deep learning model fusing MobileNetV3, DenseNet121, and DINOv2 achieved up to 99.3% accuracy in classifying five types of ...
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© 2025 Scienmag - Science Magazine