Ping Yu

Assoc. Professor

University of Wollongong

Australia

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About

Ping Yu is an Associate Professor at the University of Wollongong, Australia. His research focuses on social media crisis communication, supportive care needs in pancreatic cancer patients, and the application of large language models in healthcare information extraction. Recent publications highlight his work on nursing care quality improvement systems and the prevalence of mental health issues among dementia patients in residential facilities.

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2022

Collaborators (16)

Lynn Gribble

Associate Professor

UNSW Sydney

AUSTRALIA

Ping Yu

Research Interests

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About

Articles (30)

A Digital Alert Feedback System (Aged Care Electronic Dashboard Information Tool, ACED‐IT) to Enhance Quality Nursing Care: Participatory Action Research

Social media crisis communication and public engagement during COVID-19 analyzing public health and news media organizations’ tweeting strategies

Supportive Care Needs and Related Interventions in Patients with Pancreatic Cancer and Their Informal Caregivers: A Scoping Review

A comprehensive evaluation of large language models for information extraction from unstructured electronic health records in residential aged care

Leveraging Retrieval Augmented Generation-Driven Large Language Models to Extract Dementia Agitation Symptoms and Triggers from Free-Text Nursing Notes

Prevalence of Agitation and Depression Amongst People with Dementia in Australian Residential Aged Facilities: A Cross-Sectional Study Using LLMs

Predicting 28-day all-cause unplanned hospital re-admission of patients with alcohol use disorders: a machine learning approach

Adapting Generative Large Language Models for Information Extraction from Unstructured Electronic Health Records in Residential Aged Care: A Comparative Analysis of Training Approaches

Adapting Generative Large Language Models for Information Extraction from Unstructured Electronic Health Records in Residential Aged Care: A Comparative Analysis of Training Approaches

Development, Validation, and Application of the Electronic Frailty Index: A Scoping Review

Developing an ontology of non-pharmacological treatment for emotional and mood disturbances in dementia

Microglia Caspase11 non-canonical inflammasome drives fever

Applying generative AI with retrieval augmented generation to summarize and extract key clinical information from electronic health records

Challenges and Opportunities of Artificial Intelligence in CDSS and Patient Safety.

Three-Dimension Inversion of Magnetic Data Based on Multi-Constraint UNet plus

Does air pollution fuel irrational behaviors in stock investments?

An Empirical Study on Automated Test Generation Tools for Java: Effectiveness and Challenges

A community-based practice for the co-development of women academic leaders

Automatic quantitative stroke severity assessment based on Chinese clinical named entity recognition with domain-adaptive pre-trained large language model

Academic Women Co-designing Education Futures in a Postdigital World

Malnutrition and its contributing factors for older people living in residential aged care facilities: Insights from natural language processing of aged care records.

Constrained optimization for stratified treatment rules in reducing hospital readmission rates of diabetic patients

Development of a composite healthy ageing score: evidence from middle-to-older aged Australians

Green space type and healthy ageing in place: An Australian longitudinal study

Equivalence of two least-squares estimators for indirect effects

Impact of an emergency department rapid response system on inpatient clinical deterioration: A controlled pre-post study

Validity and reliability of the Persian version of the Patient readiness to engage in health information technology (PRE-HIT) instrument

Research on the Evolution of Consumers' Purchase Intention Based on Online Reviews and Opinion Dynamics

Green Space and Inequities in Healthy Ageing: Are Grasses Greener on the Socioeconomically Advantaged Side?

Novel nested patch-based feature extraction model for automated Parkinson's Disease symptom classification using MRI images

Collaborators (16)

Lynn Gribble

Nathan Martin D'Cunha

isabelle Lys

Elisa Bone

Chao Deng

Chris Campbell

Elaine Huber

Wenjing Jia

Lina Markauskaite

Xiaoqi Feng

Thomas Astell-Burt

Camille Dickson-Deane

Ching-Chi Yang

Lucila Carvalho

Stephen Isbel

Kasia Bail

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