Skip to main content
Yong Yin on Muck Rack

Yong Yin

As seen in: Medium, Nature, Wiley Online Library, British Pharmacological Society, PLOS ONE, Frontiers, Frontiers in Public Health, MDPI, Taylor & Francis Online, Royal Society of Chemistry and
Is this you? 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. Claim your profile

Get in touch with Yong

Contact Yong, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

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.
Claim your profile

Articles

Meteorological factors modulate idiopathic epistaxis risk: a 12-year retrospective study in Changshu

|
By Chao Yu, Xueting Fu, Lian Gu, Yong Yin, Zhen Wu, Hao Wu
| Frontiers in Public Health Verified
Abstract Objective: To investigate the incidence of idiopathic epistaxis in Changshu, China, and its correlations with meteorological factors. Methods: We retrospectively enrolled 24,193 patients with idiopathic epistaxis from March 2011 to November 2022. Matched clinical, population, and meteorological data were analyzed. Spearman’s correlation and variance inflation factor analyses were performed to assess multicollinearity.
Open in Who Shared Issue with article?

Development and validation of an explainable model for Mycoplasma pneumoniae infection in children

|
By Xin Yang, Liwen Zhang, Yong Yin, Hejun Jiang, Guijun Yang, Zhichao Sun, Yunqin Zhang, Juan Cui, Guifang Zhou, Na Wang, JING CHEN
| Nature Verified
Abstract This study aimed to develop an explainable early diagnostic model for Mycoplasma pneumoniae (MP) infection in children and assess clinicians’ perceptions before and after its deployment. Data were collected from children with acute fever or cough at Linyi Maternal and Child Healthcare Hospital and Shanghai Children’s Medical Center in 2023.
Open in Who Shared Issue with article?

GAN-PD: generative adversarial networks for fabric defect generation towards precise detection

|
By Yuyang Xia, Yong Yin, Fengkai Luan, Junqi Liu, Jiaxing Yang
| Nature Verified
Abstract Automated inspection of textile surfaces is challenged by the scarcity and geometric intricacy of real defect samples, especially the elongated, sub-millimetre scratches critical for quality grading. Existing generative approaches often prioritize image realism, thereby neglecting the geometric continuity and contextual fidelity essential for robust detection by modern systems.
Open in Who Shared Issue with article?
See all 49 licensed articles (58 Total)