Titlebook: Computational Mathematics Modeling in Cancer Analysis; Third International Jia Wu,Wenjian Qin,Boklye Kim Conference proceedings 2025 The E

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书目名称Computational Mathematics Modeling in Cancer Analysis读者反馈学科排名

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Multi-channel Multi-model Fusion Module (MMFM) Based Circulating Abnormal Cells (CACs) Detection founder each channel. Previous studies have utilized instance segmentation and target detection algorithms to identify cells and signal points in four-color fluorescence in situ hybridization (FISH) microscopy images. However, these algorithms require high accuracy in cell edge segmentation and signal

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,Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation,e disentanglement is a classic solution to this purpose, where the extracted task-related feature is presumed to be resilient to domain shift. However, the absence of references from other domains in a single-domain scenario poses significant uncertainty in feature disentanglement (.). In this paper

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Attention-Fusion Model for Multi-omics (AMMO) Data Integration in Lung Adenocarcinoma,tanding of interactions among different omics data remains unknown, current methods do not consider the unique and similar properties. In this paper, we propose Attention-fusion Model for Multi-Omics (AMMO), a robust method that addresses this challenge through domain separation. Our proposed attent

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PD-L1 Expression Prediction Using Scalable Multi Instance Transformer,t clinical standard for initiating ICI therapy is the assessment of Programmed Death-Ligand 1 (PD-L1) status via immunohistochemistry (IHC) on biopsy specimens. However, this invasive procedure presents risks and limitations, highlighting the need for a non-invasive alternative. This study retrospec

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,Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical linical applications. Data augmentation plays an important role in improving the diversity of training data. Recent data augmentation methods aim to randomize or disrupt the texture of images to encourage models to focus more on shape features, which are considered domain-invariant. It’s worth notin

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