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Ziying Li

As seen in: Nature, Wiley Online Library, Cambridge University Press & Assessment, Journal of Automated Methods and Management in Chemistry, Frontiers, MDPI, SAGE Publishing, Taylor & Francis Online, ACS Publications, Royal Society of Chemistry and
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Articles

Deep knowledge-driven multi-modal fusion for diagnosis and prognosis of SI-ARDS

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By Hongyi Chen, Yang Gu, Guangwei Zhang, Yan Zhang, Xiaohui Duan, Ziying Li, Jiaqi Lin, Xiaoling Yi, Mansheng Chen, Tianqi Yang, Xuanqi Huang, Guoqiong Zeng, Huijun Hu, Riyu Han, Hao Wu, Peiyuan Lai, Changdong Wang, Yunfang Yu, Tao Yu, Mohsen Guizani, Leqi Zheng
| Nature Verified
Abstract Sepsis-Induced Acute Respiratory Distress Syndrome (SI-ARDS) presents significant diagnostic and prognostic challenges due to its complex clinical manifestations and high mortality rate. We developed a deep Knowledge-Driven multi-Modal Fusion (KDMF) framework for the accurate diagnosis and prognosis of SI-ARDS. The model leverages multi-modal data, including CT images, CT reports, and laboratory indicators, alongside a disease-specific knowledge graph.
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La integración bidireccional de los inmigrantes chinos en el Perú: una perspectiva histórico-sociológica

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By Ziying Li, Manyao Li
| Dialnet - Universidad de La Rioja
IdiomacatalàDeutschEnglishespañoleuskarafrançaisgalegoitalianoportuguêsromână
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Dose rounding of trastuzumab deruxtecan in chinese patients: cost savings and safety outcomes in real-world study

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By Ziying Li, Ziyuan Zhou, Lingzhi Ren, Chengsheng Xie, Jun Meng, Guohui Li, Haochun Tang
| Frontiers
Abstract Trastuzumab deruxtecan is a life-saving but costly therapy for HER2-positive cancers. While dose rounding strategies have been proposed to reduce drug waste, their safety and cost-saving potential in real-world Chinese patients remain understudied. This study aimed to evaluate the cost savings of dose rounding for trastuzumab deruxtecan in China and compare the safety profiles of upward rounding, downward rounding, and no rounding groups.
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