ascopubs.org

Transformer-based deep learning model for integrated pathomics and radiomics in predicting postoperative survival of intrahepatic cholangiocarcinoma patients.

Hepatocellular carcinoma patients with portal vein thrombosis treated with robotic radiosurgery for long term outcome and analysis: CTRT:2022/01/050234. This is an ASCO Meeting Abstract from the 2025 ...
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A novel deep learning model for medical image segmentation with convolutional neural network and transformer

Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...
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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

CGMformer is first self-supervised pretrained on CGM data to gain fundamental knowledge of the glucose dynamics, and then applied to a multitude of downstream clinical applications. The extractable ...
ascopubs.org

Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non–Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...