Yingyong Hou
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As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Articles
Retraction Note: Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma
Retraction Note to: Nature Communications https://doi.org/10.1038/s41467-024-45306-y, published online 15 February 2024 The authors have retracted this article. After publication, concerns were raised regarding potential similarities between Figs. 2F-1 and 2J-4; Figs. 2I-4 and 2J-1; Figs. 2I-1 and 3L-1; Figs. 2I-3 and 2J-2; Fig. 2I-4 and Supplementary Fig. 10B-4; Figs. 2J-1 and 3L-1; Figs. 2J-3 and 3L-2; Supplementary Figs. 7C-25 and 7C-5; Supplementary Figs. 10B-1 and 10B-3; Supplementary Figs.
Foundation Model‐Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi‐Institutional Retrospective Study
1 Introduction Accurate prognostic prediction for colorectal cancer (CRC), encompassing both survival rates and disease progression, is of paramount importance for guiding treatment decisions and follow-up strategies. Nevertheless, it still remains a significant challenge [1-5]. Current methods, such as the AJCC and TNM staging, predominantly depend on pathological staging approaches that are inherently subjective and quite limited, frequently neglecting individual patient-specific data.
High-grade uterine endometrial stromal sarcoma harboring GLI1 and MDM2/CDK4 co-amplifications - Diagnostic Pathology
This retrospective study was performed with the approval of Zhongshan Hospital, Fudan University review board. The pathology files were searched for endometrial stromal sarcomas (ESS) of surgical specimens in female patients from January 2016 to August 2022 including inpatient pathology and consultation pathology records. A total of 31 cases of ESS (20 LGESS and 11 HGESS), 1 uterine adenosarcoma (sarcoma component is HGESS) were included.
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