Yue Wang

ORCID: 0000-0001-5502-8498
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About
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Research Areas
  • Artificial Intelligence in Healthcare and Education
  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • Machine Learning in Healthcare
  • Traditional Chinese Medicine Studies
  • Gestational Diabetes Research and Management
  • Pregnancy and preeclampsia studies
  • Digital and Traditional Archives Management
  • Pregnancy-related medical research

Shanghai Electric (China)
2024

Sun Yat-sen University
2023

Key Laboratory of Guangdong Province
2023

Sun Yat-sen Memorial Hospital
2023

Jilin University
2021-2022

First Hospital of Jilin University
2021-2022

Tianjin Children's Hospital
2013

The aim of the present study was to evaluate single and joint associations maternal prepregnancy body mass index (BMI) gestational weight gain (GWG) with pregnancy outcomes in Tianjin, China.Between June 2009 May 2011, health care records 33,973 pregnant women were collected their children measured for birth length. independent BMI GWG based on Institute Medicine (IOM) guidelines risks neonatal examined by using Logistic Regression.After adjustment all confounding factors, positively...

10.1371/journal.pone.0082310 article EN cc-by PLoS ONE 2013-12-20

ChatGPT, an artificial intelligence (AI) system powered by large-scale language models, has garnered significant interest in healthcare. Its performance dependent on the quality and quantity of training data available for a specific language, with majority it being English. Therefore, its effectiveness processing Chinese which fewer available, warrants further investigation. This study aims to assess ChatGPT's ability medical education clinical decision-making within context. We utilized...

10.1371/journal.pdig.0000397 article EN cc-by PLOS Digital Health 2023-12-01

Abstract Background ChatGPT, an artificial intelligence (AI) system powered by large-scale language models, has garnered significant interest in the healthcare. Its performance dependent on quality and amount of training data available for specific language. This study aims to assess ChatGPT’s ability medical education clinical decision-making within Chinese context. Methods We utilized a dataset from National Medical Licensing Examination (NMLE) ChatGPT-4’s proficiency knowledge Performance...

10.1101/2023.05.03.23289443 preprint EN medRxiv (Cold Spring Harbor Laboratory) 2023-05-05

Abstract As a critical component of information management, the development digital and archive systems enhances both efficiency quality enterprise operations, thereby increasing economic value. This paper employs ReLU activation function to augment non-linear capabilities neural network model. Additionally, we introduce MP-CNN model, designed extract recognize textual content from archival images. These images are initially processed using BP algorithm, followed by grayscale conversion for...

10.2478/amns-2024-1405 article EN Applied Mathematics and Nonlinear Sciences 2024-01-01

Abstract Background The ChatGPT, a Large-scale language models-based Artificial intelligence (AI), has fueled interest in medical care. However, the ability of AI to understand and generate text is constrained by quality quantity training data available for that language. This study aims provide qualitative feedback on ChatGPT’s problem-solving capabilities education clinical decisionmaking Chinese. Methods A dataset Clinical Medicine Entrance Examination Chinese Postgraduate was used assess...

10.1101/2023.04.12.23288452 preprint EN medRxiv (Cold Spring Harbor Laboratory) 2023-04-18

<sec> <title>BACKGROUND</title> ChatGPT, an artificial intelligence (AI) system powered by large-scale language models, has garnered significant interest in the healthcare. Its performance dependent on quality and amount of training data available for specific language. This study aims to assess ChatGPT's ability medical education clinical decision-making within Chinese context. </sec> <title>OBJECTIVE</title> Evaluate NMLE conducted <title>METHODS</title> We utilized a dataset from National...

10.2196/preprints.48698 preprint EN 2023-05-03

<sec> <title>BACKGROUND</title> With the accumulation of electronic health records and development artificial intelligence, patients with cancer urgently need new evidence more personalized clinical demographic characteristics sophisticated treatment prevention strategies. However, no research has systematically analyzed application significance intelligence based on in care. </sec> <title>OBJECTIVE</title> The aim this study was to conduct a review introduce current state limitations...

10.2196/preprints.33799 preprint EN 2021-09-24
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