Area of research
Molecular Biology · Artificial Intelligence
Research interest
Research interests include Pseudomonas aeruginosa, Medicine, Computer science, Materials science, Quorum sensing, and Microbiology.
Study on the corrosion damage behavior and anti-corrosion methods of mining anchor cables in high-mineralized water environments
Preliminary analysis of the impact of lab results on large language model generated differential diagnoses
Design, Synthesis, and Biological Evaluation of Asymmetrical Disulfides Based on Garlic Extract as <i>Pseudomonas aeruginosa pqs</i> Quorum Sensing Inhibitors
Improving Large Language Models’ Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation
Ontology enrichment using a large language model: Applying lexical, semantic, and knowledge network-based similarity for concept placement
Synoptic reporting by summarizing cancer pathology reports using large language models
Psychosocial considerations in pediatric heart transplantation: Initial validation of the Pediatric Psychosocial Assessment Tool at a single center
Enhancing patient engagement and understanding: is providing direct access to laboratory results through patient portals adequate?
Predicting Organ Rejections for Pediatric Heart Transplantations with a Combined Use of Transplant Registry Data and Electronic Health Records
Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study
Structure-Based Discovery of Symmetric Disulfides from Garlic Extract as <i>Pseudomonas aeruginosa</i> Quorum Sensing Inhibitors
Discovery of novel amide derivatives as potent quorum sensing inhibitors of Pseudomonas aeruginosa
Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction
Design and Synthesis of Aryl Amide Derivatives Containing Thiazole as Type III Secretion System Inhibitors against <i>Pseudomonas aeruginosa</i>
Enhancing patient Comprehension: An effective sequential prompting approach to simplifying EHRs using LLMs
Predicting Adherence to Computer-Based Cognitive Training Programs Among Older Adults: Study of Domain Adaptation and Deep Learning
Synoptic Reporting by Summarizing Cancer Pathology Reports using Large Language Models
Tipping point analysis for the between-arm correlation in an arm-based evidence synthesis
Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study.
New opportunities for the early detection and treatment of cognitive decline: adherence challenges and the promise of smart and person-centered technologies
Enriching Real-world Data with Social Determinants of Health for Health Outcomes and Health Equity: Successes, Challenges, and Opportunities
Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model
Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches
Editorial: Explainable artificial intelligence for critical healthcare applications
Improving Adherence to a Mediterranean Ketogenic Nutrition Program for High-Risk Older Adults: A Pilot Randomized Trial
Towards Interpretable Multimodal Predictive Models for Early Mortality Prediction of Hemorrhagic Stroke Patients.
PubMed 2023cited by 9position: last
Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records
Big advocacy, little recognition: the hidden work of Black patients in precision medicine
Benchmarking Transformer-Based Models for Identifying Social Determinants of Health in Clinical Notes
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke