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Ying Xiao

As seen in: Nature, Wiley Online Library, PLOS ONE, ScienceDirect, Annals of the Rheumatic Diseases, Frontiers, Frontiers in Public Health, Healthcare Magazine MDPI, MDPI, Taylor & Francis Online and
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Articles

A scoping review of bias in large AI models for medicine and healthcare

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By Ying Xiao, Zhenpeng Chen, Jen-tse Huang, Wenting Chen, Yepang Liu, Kezhi Li, Mohammad Reza Mousavi, Richard J. B. Dobson, Jie Zhang
| Nature Verified
Abstract Traditional AI models and large AI models, such as large language models, represent fundamentally distinct paradigms. Large AI models have demonstrated expert-level performance in specific medical domains. However, concerns about medical bias have attracted growing attention from the medicine, sociology, and AI communities.
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Machine learning-assisted detection of Sudan I in chili powder using FT-IR coupled with magnetic molecular imprinting extraction

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By Yichen Zhang, Zihan Chen, Paolo Coghi, Xiao Feng, Zhanming Li, Tian Zhong, Ying Xiao, Peng Gao, Xi Yu
| Nature Verified
Abstract This study presents a rapid and selective analytical method for the quantification of Sudan I in chili powder by integrating magnetic molecularly imprinted solid-phase extraction (MISPE) with machine learning (ML)-assisted Fourier transform infrared (FTIR) spectroscopy.
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Engineering Solvation Sheath and Gradient Interphase via Pull-Expulsion Dynamics for Low-Temperature Quasi-Solid-State Sodium Metal Batteries

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By Wanting Wu, Ying Xiao, Ruxue Ruan
| Wiley Online Library Verified
1 Introduction Sodium metal batteries (SMBs) have emerged as promising candidates for large-scale energy storage, driven by the natural abundance and low cost of sodium resources, as well as the high theoretical capacity of sodium metal anodes [1, 2].
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