Matthew M Ruppert

Matthew M Ruppert,

OPS Data Scientist

Department: MD-SURGERY-TRAUMA
Business Phone: (352) 273-5670
Business Email: ruppert20@ufl.edu

About Matthew M Ruppert

Research Profile

Open Researcher and Contributor ID (ORCID)

0000-0001-9757-4454

Areas of Interest
  • Acute care surgery
  • Artificial Intelligence
  • Clinical Decision Support Adjuncts
  • Critical Care Management
  • Critical care monitoring
  • Nephrology
  • Sepsis
  • Surgery

Publications

Academic Articles
2024
Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery.
Annals of surgery open : perspectives of surgical history, education, and clinical approaches. 5(2) [DOI] 10.1097/AS9.0000000000000429. [PMID] 38911666.
2024
Community-engaged artificial intelligence research: A scoping review.
PLOS digital health. 3(8) [DOI] 10.1371/journal.pdig.0000561. [PMID] 39178307.
2024
Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients.
PloS one. 19(4) [DOI] 10.1371/journal.pone.0299332. [PMID] 38652731.
2024
Electronic Health Record Data Quality and Performance Assessments: Scoping Review.
JMIR medical informatics. 12 [DOI] 10.2196/58130. [PMID] 39504136.
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.
2024
Intraoperative hypotension and postoperative acute kidney injury: A systematic review.
American journal of surgery. 232:45-53 [DOI] 10.1016/j.amjsurg.2024.02.001. [PMID] 38383166.
2024
Risk-Specific Training Cohorts to Address Class Imbalance in Surgical Risk Prediction.
JAMA surgery. 159(12):1424-1431 [DOI] 10.1001/jamasurg.2024.4299. [PMID] 39382865.
2023
A deep learning-based dynamic model for predicting acute kidney injury risk severity in postoperative patients.
Surgery. 174(3):709-714 [DOI] 10.1016/j.surg.2023.05.003. [PMID] 37316372.
2023
Building an automated, machine learning-enabled platform for predicting post-operative complications.
Physiological measurement. 44(2) [DOI] 10.1088/1361-6579/acb4db. [PMID] 36657179.
2023
Clinical Courses of Acute Kidney Injury in Hospitalized Patients: A Multistate Analysis.
ArXiv. [PMID] 36945689.
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 predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks.
Scientific reports. 13(1) [DOI] 10.1038/s41598-023-27418-5. [PMID] 36681755.
2023
Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review.
JMIR medical informatics. 11 [DOI] 10.2196/48297. [PMID] 37646309.
2023
Overtriage, Undertriage, and Value of Care after Major Surgery: An Automated, Explainable Deep Learning-Enabled Classification System.
Journal of the American College of Surgeons. 236(2):279-291 [DOI] 10.1097/XCS.0000000000000471. [PMID] 36648256.
2023
Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care.
Annals of surgery. 277(2):179-185 [DOI] 10.1097/SLA.0000000000005460. [PMID] 35797553.
2023
Predictive Modeling for Readmission to Intensive Care: A Systematic Review.
Critical care explorations. 5(1) [DOI] 10.1097/CCE.0000000000000848. [PMID] 36699252.
2023
Retrospective value assessment of a dedicated, trauma hybrid operating room.
The journal of trauma and acute care surgery. 94(6):814-822 [DOI] 10.1097/TA.0000000000003873. [PMID] 36727772.
2022
A framework for a consistent and reproducible evaluation of manual review for patient matching algorithms.
Journal of the American Medical Informatics Association : JAMIA. 29(12):2105-2109 [DOI] 10.1093/jamia/ocac175. [PMID] 36305781.
2022
Aligning Patient Acuity With Resource Intensity After Major Surgery: A Scoping Review.
Annals of surgery. 275(2):332-339 [DOI] 10.1097/SLA.0000000000005079. [PMID] 34261886.
2022
Federated learning for preserving data privacy in collaborative healthcare research.
Digital health. 8 [DOI] 10.1177/20552076221134455. [PMID] 36325438.
2022
Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible.
PLOS digital health. 1(1) [DOI] 10.1371/journal.pdig.0000006. [PMID] 36532301.
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.
2022
Uncertainty-aware deep learning in healthcare: A scoping review.
PLOS digital health. 1(8) [DOI] 10.1371/journal.pdig.0000085. [PMID] 36590140.
2021
Advances in artificial intelligence and deep learning systems in ICU-related acute kidney injury.
Current opinion in critical care. 27(6):560-572 [DOI] 10.1097/MCC.0000000000000887. [PMID] 34757993.
2021
Association of Postoperative Undertriage to Hospital Wards With Mortality and Morbidity.
JAMA network open. 4(11) [DOI] 10.1001/jamanetworkopen.2021.31669. [PMID] 34757412.
2021
Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU.
Frontiers in digital health. 3 [DOI] 10.3389/fdgth.2021.640685. [PMID] 33718920.
2021
Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review.
Annals of surgery. 273(2):258-268 [DOI] 10.1097/SLA.0000000000003935. [PMID] 32482979.
2021
Pain Action Unit Detection in Critically Ill Patients.
Proceedings : Annual International Computer Software and Applications Conference. COMPSAC. 2021:645-651 [DOI] 10.1109/compsac51774.2021.00094. [PMID] 34723289.
2021
Reinforcement learning in surgery.
Surgery. 170(1):329-332 [DOI] 10.1016/j.surg.2020.11.040. [PMID] 33436272.
2020
Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension.
The Journal of surgical research. 254:350-363 [DOI] 10.1016/j.jss.2020.05.007. [PMID] 32531520.
2020
Cardiovascular death and progression to end-stage renal disease after major surgery in elderly patients.
BJS open. 4(1):145-156 [DOI] 10.1002/bjs5.50232. [PMID] 32011817.
2020
ICU Delirium-Prediction Models: A Systematic Review.
Critical care explorations. 2(12) [DOI] 10.1097/CCE.0000000000000296. [PMID] 33354672.
2020
Improving the Intensive Care Patient Experience With Virtual Reality-A Feasibility Study.
Critical care explorations. 2(6) [DOI] 10.1097/CCE.0000000000000122. [PMID] 32695991.
2020
The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review.
F1000Research. 9 [DOI] 10.12688/f1000research.25769.2. [PMID] 36110837.
2019
Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: A pilot usability study.
Surgery. 165(5):1035-1045 [DOI] 10.1016/j.surg.2019.01.002. [PMID] 30792011.
2019
Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics.
PloS one. 14(4) [DOI] 10.1371/journal.pone.0214904. [PMID] 30947282.
2019
Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning.
Scientific reports. 9(1) [DOI] 10.1038/s41598-019-44004-w. [PMID] 31142754.
2016
Preoperative assessment of the risk for multiple complications after surgery.
Surgery. 160(2):463-72 [DOI] 10.1016/j.surg.2016.04.013. [PMID] 27238354.

Education

Doctor of Medicine – MD
2022-2026 · University of Central Florida College of Medicine
Master of Science in Medical Sciences, Biomedical Informatics
2020-2022 · University of Florida
Graduate Certificate in Medical Anatomy and Physiology
2019-2020 · University of Florida
Bachelor of Science in Biomedical Engineering
2014-2018 · University of Florida

Contact Details

Phones:
Business:
(352) 273-5670
Emails:
Business:
ruppert20@ufl.edu
Addresses:
Business Mailing:
PO Box 103450
GAINESVILLE FL 32610
Business Street:
1600 SW ARCHER RD
GAINESVILLE FL 32610