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Yuan Shen on Muck Rack

Yuan Shen

As seen in: Color Research & Application, Forbes, Nature, Wiley, Wiley Online Library, BMJ Open, MDPI, ACS Publications, Science Magazine, Royal Society of Chemistry and
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Articles

Bile Drainage Improves Survival in Amatoxin-induced Severe Liver Injury: A Prospective Pilot Cohort Study

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By Xiuying Ma, Wei Yue, Yuan Shen
| Xia & He Publishing Inc. Verified
Amatoxin-containing mushroom poisoning is a life-threatening medical emergency with a persistently high mortality rate. Although cases are relatively uncommon, they occur worldwide—particularly in regions where foraging is prevalent—and can progress from initial gastrointestinal symptoms to fulminant hepatic failure within days after ingestion. It typically produces gastrointestinal symptoms within 6–24 h and acute liver failure within three to five days.
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Anesthetics as emerging therapeutics for post-traumatic stress disorder (PTSD): bridging bench and bedside

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By Haitao Wu, Tifei Yuan, James Samsom, Siqi Ying, Xin Zhe Liu, Tianle Xu, Fang Liu, Yuan Shen, Xinchun Mei
| Nature Verified
Abstract Post-traumatic stress disorder (PTSD) is a severe psychiatric disorder that develops in the months and years following exposure to severe trauma. Despite growing research, there remain gaps in understanding the full pathophysiology of PTSD, so that treatments are not universally effective, contributing to a significant public health burden. Therefore, it is necessary to explore novel therapeutic approaches.
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Design of packaging style recommendation system based on user behavior analysis and emotional feature extraction

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By Pan CL, Yuan Shen, Renwei Li, Xin Cao
| PeerJ
The recommendation system analyzes user behavior data, identifies their interests and hobbies, and provides accurate services to users. Recommendation algorithms are mainly divided into four categories: content-based methods, rating matrix methods, user behavior methods, and sentiment feature methods. Content based recommendation methods mainly rely on users’ historical interests to recommend relevant products to them.
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