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Yining Hua

As seen in: Wiley Online Library, medRxiv
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Articles

From statistics to deep learning: Using large language models in psychiatric research

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By Yining Hua, Andrew Beam, Lori B. Chibnik, John Torous Verified
| Wiley Online Library Verified
1 INTRODUCTION The integration of Large Language Models (LLMs) into psychiatry and mental health research is poised to revolutionize the field by enhancing diagnostic accuracy, personalizing care, and streamlining administrative tasks (Hua et al., 2024; Obradovich et al., 2024; Zhou et al., 2023). LLMs can efficiently process vast amounts of data, summarize clinical notes, and assist in complex decision-making processes (Yu et al., 2023).
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Standardizing and Scaffolding Healthcare AI-Chatbot Evaluation

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By Yining Hua, David Bates, Winna Xia, Luke Hartstein
| medRxiv
JT reports grants from Otsuka and is an advisor to Precision Mental Wellness, outside of the submitted work. DWB reports grants and personal fees from EarlySense, personal fees from CDI Negev, equity from ValeraHealth, equity from Clew, equity from MDClone, personal fees and equity from AESOP, personal fees and equity from Feelbetter, equity from Guided Clinical Solutions, and grants from IBM Watson Health, outside the submitted work.
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Denoising Longitudinal Social Media for Pandemic Monitoring

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By Shixu Lin, Yining Hua, Zhijiang Guo, Lucas Garay
| medRxiv
The authors have declared no competing interest. This research received no specific grant from any funding agency in public, commercial or not-for-profit sectors. I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
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