Ensemble AI Reads Brain MRI With Adaptive Attention and Statistical Rigor
A class-adaptive ensemble of three neural networks classifies brain tumors in MRI scans with 99.39 percent benchmark accuracy, validated by ...
A class-adaptive ensemble of three neural networks classifies brain tumors in MRI scans with 99.39 percent benchmark accuracy, validated by ...
A hybrid TransUNet–DenseNet121 deep learning framework classifies brain tumors from MRI scans with reported accuracies up to 99.56 percent while ...
An explainable transformer model fusing MRI with texture descriptors reached over 99 percent accuracy in Alzheimer's disease staging benchmarks, with ...
A new open-access review in Cancer Nanotechnology surveys how nanomaterials could improve colorectal cancer diagnosis, targeted therapy, and personalized theranostics.
Within two weeks of diabetes onset, rats showed significantly disorganized femoral collagen fibers despite unchanged bone mineral measures, with the ...
A new perspective article argues that MRI's development for cancer detection rested on multiple research groups and a key discovery ...
In a cross-sectional study of 100 multiple sclerosis patients, 3-Tesla double inversion recovery MRI detected more cervical cord lesions with ...
A prospective comparative study found ACL T2* mapping values increased significantly across MRI-defined normal, partial-tear, and complete-tear categories, though diagnostic ...
A new 3D Mamba-based model segments brain tumors with consistent accuracy gains and a 15x efficiency improvement over existing state-of-the-art ...
A 13-year-old boy's frontal-lobe white matter disease, initially suspected to be Alexander disease, was diagnosed as Wilson's disease after genetic ...
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© 2026 Scienmag - Science Magazine