AI Reads Breast MRI With Striking Accuracy, But a New Meta-Analysis Urges Caution
A new meta-analysis of 18 studies finds that deep learning applied to dynamic contrast-enhanced breast MRI achieves 90 percent sensitivity ...
A new meta-analysis of 18 studies finds that deep learning applied to dynamic contrast-enhanced breast MRI achieves 90 percent sensitivity ...
A new study shows that synthetic relative T1/T2 maps reconstructed from routine MRI sequences modestly but consistently improve U-Net-based segmentation ...
A prospective study of 412 children found that GPT-5.2 Instant missed nearly half of elbow fractures on radiographs, with sensitivity ...
A phantom study shows that the direction of breast compression in prone tomosynthesis-guided vacuum-assisted biopsy significantly affects device warnings and ...
A comprehensive Heliyon benchmark of 16 survival prediction methods and 12 feature engineering strategies across three radiomic datasets finds that ...
A retrospective study of 168 patients links higher non-perfused volume ratio after HIFU ablation of uterine fibroids to greater symptom ...
A new AI framework called BAMR-HF combines boundary-aware segmentation, radiomic–deep feature fusion, and contextual modeling to segment and classify lung ...
Every year, acute lymphoblastic leukemia claims thousands of lives, many of them children, and the first clue to its presence ...
A new deep learning model combines diffusion-style state propagation with Mamba-based sequence modeling and window attention to grade ulcerative colitis ...
A new calibration-aware Vision Transformer framework classifies brain tumor MRI scans with over 98 percent accuracy while flagging uncertain cases ...
A German research team has shown that a GLM-based residualization method removes age confounding from MRI-based Alzheimer's classifiers far more ...
Researchers show that routine chest CT scans, combined with machine learning analysis of body composition and clinical data, can opportunistically ...
A new deep learning network called MALCNet reconstructs missing MRI information in the latent space, achieving statistically significant gains in ...
Researchers in Thailand have developed an explainable deep learning system that diagnoses five causes of vaginal discharge from smartphone photos ...
A 3D multi-scale convolutional neural network developed in Taiwan accurately segments and quantifies acute ischemic stroke lesions on diffusion-weighted MRI ...
A TransUNet-inspired deep learning system segmented hernia defects and abdominal wall muscles on 215 CT scans with IoU values of ...
A deep learning model that reads multiregional contrast-enhanced breast MRI can predict whether chemotherapy has completely cleared the axillary lymph ...
Worcester Polytechnic Institute researchers finished third out of 181 teams in an international AI competition with TwinSight, a dual deep-learning ...
A new asymmetric AI fusion framework that treats dermoscopic images as the primary representation and clinical photos as a corrective ...
A narrative review argues that quantum-inspired algorithms, cloud computing, and edge processors could replace static ultrasound safety indices with dynamic, ...
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