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Chao You

Fudan University Shanghai Cancer Center
H-index:19
Citation Count:1,042
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Deep learning synthesis of DBT features from mammography for breast cancer diagnosis

基于乳腺X光图像的深度学习DBT特征合成用于乳腺癌诊断

2025-10-230
PRE
Head‑to‑head comparison of contrast‑enhanced mammography and MRI in assessing the tumor response to neoadjuvant therapy in breast cancer: a prospective, multireader study

对比增强乳腺摄影与MRI在评估乳腺癌新辅助治疗效果中的头对头比较:一项前瞻性、多读者研究

2025-08-120
PRE
A Dynamic Contrast-Enhanced MRI-Based Vision Transformer Model for Distinguishing HER2-Zero, -Low, and -Positive Expression in Breast Cancer and Exploring Model Interpretability

p:e03925

2025-06-090
OAAI
Influence of Multiband Technique on Temporal Diffusion Spectroscopy and Its Diagnostic Value in Breast Tumors
2025-01-311
OA
Whole tumour- and subregion-based radiomics of contrast-enhanced mammography in differentiating HER2 expression status of invasive breast cancers: A double-centre pilot study
2024-10-091
PRE
Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection

多中心放射多组学分析可预测乳腺癌的预后并阐明成像与生物学的联系

2024-09-071
OAAI
Radiomics in breast cancer: Current advances and future directions

乳腺癌的放射组学: 当前进展和未来方向

2024-09-011
OAAI
A preoperative radiogenomic model based on quantitative heterogeneity for predicting outcomes in triple-negative breast cancer patients who underwent neoadjuvant chemotherapy

基于定量异质性的术前放射基因组学模型预测接受新辅助化疗的三阴性乳腺癌患者的预后

2024-07-303
OAAI
Radiomic analysis reveals diverse prognostic and molecular insights into the response of breast cancer to neoadjuvant chemotherapy: a multicohort study
2024-07-082
OAAI
Radiomics features for distinguishing true recurrence versus new primary tumor following breast-conserving treatment
2024-05-020
PRE
Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer

三阴性乳腺癌综合分子和预后分层的深度学习框架

2024-05-018
OAAI
Hybrid deep multi-task learning radiomics approach for predicting EGFR mutation status of non-small cell lung cancer in CT images

混合深度多任务学习影像组学方法预测CT图像中非小细胞肺癌EGFR突变状态

2023-12-125
PRE
Artificial intelligence in breast imaging: potentials and challenges

人工智能在乳腺成像中的应用: 潜力与挑战

2023-11-287
OA
Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

基于放射基因组学的多组学分析揭示肿瘤内异质性表型和治疗靶点

2023-10-0631
OAAI
Radiomics features for assessing tumor-infiltrating lymphocytes correlate with molecular traits of triple-negative breast cancer

用于评估肿瘤浸润淋巴细胞与三阴性乳腺癌分子特征相关的放射组学特征

2022-10-1543
OAAI
Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer

放射基因组学分析揭示三阴性乳腺癌的肿瘤异质性

2022-07-0154
OAAI
A Multiomics Signature Highlights Alterations Underlying Homologous Recombination Deficiency in Triple-Negative Breast Cancer
2022-06-167
PRE
ASO Author Reflections: Deeper Insight into Therapeutic Implications and Non-invasive Detection of Homologous Recombination Deficiency in Triple-Negative Breast Cancer: Results from a Multi-omics Cohort Study
2022-05-290
PRE
Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images
2022-05-123
OAAI