Ziyuan Guan

Ziyuan Guan,

System Manager And Data Analyst

Department: MD-MED QUANTITATIVE HEALTH
Business Phone: (352) 273-8821
Business Email: ziyuan.guan@ufl.edu

Research Profile

I am interested in Distributed Systems, System Architecture, Data Analysis with Machine Learning, and Deep Learning methods. Currently, I am passionate about optimizing systems and accelerating the processing efficiency of the complicated platforms.

Open Researcher and Contributor ID (ORCID)

0009-0009-4824-6927

Areas of Interest
  • Integration of Multi-Type, Multi-Scale Health Data
  • Intelligent systems
  • Machine learning and applications
  • data science

Publications

2024
Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures.
Scientific reports. 14(1) [DOI] 10.1038/s41598-024-59047-x. [PMID] 38600110.
2023
Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis.
Scientific reports. 13(1) [DOI] 10.1038/s41598-023-45006-5. [PMID] 37853103.
2023
Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.
… IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics. 2023 [DOI] 10.1109/bhi58575.2023.10313445. [PMID] 38585187.
2023
Machine Learning–Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review
JMIR Medical Informatics. 11:e48297-e48297 [DOI] 10.2196/48297. [PMID] 37646309.
2022
Multi-dimensional patient acuity estimation with longitudinal EHR tokenization and flexible transformer networks.
Frontiers in digital health. 4 [DOI] 10.3389/fdgth.2022.1029191. [PMID] 36440460.
2022
Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform.
JAMA network open. 5(5) [DOI] 10.1001/jamanetworkopen.2022.11973. [PMID] 35576007.
2022
Physiologic signatures within six hours of hospitalization identify acute illness phenotypes.
PLOS digital health. 1(10) [DOI] 10.1371/journal.pdig.0000110. [PMID] 36590701.

Education

Matser
2017-2019 · University of Florida
Bachelor
2013-2017 · Nanjing University Of Posts and Telecommunications

Contact Details

Phones:
Business:
(352) 273-8821
Emails:
Addresses:
Business Mailing:
PO Box 100224
GAINESVILLE FL 32610
Business Street:
PO Box 100224
GAINESVILLE FL 32610