CT-Based Deep Learning Model Stratifies Survival in Locally Advanced Esophageal Carcinoma
A deep learning framework combining latent diffusion models and 3D Vision Transformers can segment tumors and predict survival differences in ...
A deep learning framework combining latent diffusion models and 3D Vision Transformers can segment tumors and predict survival differences in ...
A comprehensive narrative review establishes that molecular PET/CT imaging for pancreatic masses must be guided by suspected tumor biology and ...
An attention-enhanced ResNet-50 deep learning model achieved an accuracy of 0.833 and an area under the curve of 0.855 when ...
A retrospective study demonstrates that five-cluster CT habitat analysis outperforms whole-lesion radiomics in differentiating hemorrhagic transformation from contrast extravasation after ...
A comparative bibliometric analysis across Scopus, Web of Science, and PubMed found artificial intelligence research on triple-negative breast cancer expanded ...
A deep learning framework that decodes spatial intratumor heterogeneity from preoperative computed tomography scans predicts cervical lymph node metastasis and ...
A retrospective study demonstrates that a linear support vector machine analyzing first lumbar vertebra radiomic features from routine non-contrast chest ...
A narrative review examines how molecular imaging heterogeneity limits prostate cancer therapy and how artificial intelligence models may assist quantitative ...
A review in Medicine Plus evaluates artificial intelligence across osteosarcoma imaging and outlines the external validation and workflow integration required ...
A comprehensive scoping review reveals that quantitative radiomic models consistently outperform clinical-only tools in predicting gastrointestinal cancer outcomes, despite widespread ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine