2022
Development and Validation of a Risk Prediction Model for Venous Thromboembolism in Lung Cancer Patients Using Machine Learning.
Lei H, Zhang M, Wu Z, Liu C, Li X, Zhou W, Long B, Ma J, Zhang H, Wang Y, Wang G, Gong M, Hong N, Liu H, Wu Y. Development and Validation of a Risk Prediction Model for Venous Thromboembolism in Lung Cancer Patients Using Machine Learning. Front Cardiovasc Med 2022, 9: 845210. PMID: 35321110, DOI: 10.3389/fcvm.2022.845210.Peer-Reviewed Original ResearchState of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review.
Hong N, Liu C, Gao J, Han L, Chang F, Gong M, Su L. State of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review. JMIR Med Inform 2022, 10: e28781. PMID: 35238790, DOI: 10.2196/28781.Peer-Reviewed Original Research
2021
Early Prediction of Mortality, Severity, and Length of Stay in the Intensive Care Unit of Sepsis Patients Based on Sepsis 3.0 by Machine Learning Models.
Su L, Xu Z, Chang F, Ma Y, Liu S, Jiang H, Wang H, Li D, Chen H, Zhou X, Hong N, Zhu W, Long Y. Early Prediction of Mortality, Severity, and Length of Stay in the Intensive Care Unit of Sepsis Patients Based on Sepsis 3.0 by Machine Learning Models. Front Med (Lausanne) 2021, 8: 664966. PMID: 34291058, DOI: 10.3389/fmed.2021.664966.Peer-Reviewed Original ResearchA Clinical Prediction Model to Predict Heparin Treatment Outcomes and Provide Dosage Recommendations: Development and Validation Study.
Li D, Gao J, Hong N, Wang H, Su L, Liu C, He J, Jiang H, Wang Q, Long Y, Zhu W. A Clinical Prediction Model to Predict Heparin Treatment Outcomes and Provide Dosage Recommendations: Development and Validation Study. J Med Internet Res 2021, 23: e27118. PMID: 34014171, DOI: 10.2196/27118.Peer-Reviewed Original Research
2020
Implementation of a Cohort Retrieval System for Clinical Data Repositories Using the Observational Medical Outcomes Partnership Common Data Model: Proof-of-Concept System Validation.
Liu S, Wang Y, Wen A, Wang L, Hong N, Shen F, Bedrick S, Hersh W, Liu H. Implementation of a Cohort Retrieval System for Clinical Data Repositories Using the Observational Medical Outcomes Partnership Common Data Model: Proof-of-Concept System Validation. JMIR Med Inform 2020, 8: e17376. PMID: 33021486, DOI: 10.2196/17376.Peer-Reviewed Original Research
2019
Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries.
Hong N, Wen A, Stone DJ, Tsuji S, Kingsbury PR, Rasmussen LV, Pacheco JA, Adekkanattu P, Wang F, Luo Y, Pathak J, Liu H, Jiang G. Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries. J Biomed Inform 2019, 99: 103310. PMID: 31622801, DOI: 10.1016/j.jbi.2019.103310.Peer-Reviewed Original ResearchDeveloping a scalable FHIR-based clinical data normalization pipeline for standardizing and integrating unstructured and structured electronic health record data.
Hong N, Wen A, Shen F, Sohn S, Wang C, Liu H, Jiang G. Developing a scalable FHIR-based clinical data normalization pipeline for standardizing and integrating unstructured and structured electronic health record data. JAMIA Open 2019, 2: 570-579. PMID: 32025655, DOI: 10.1093/jamiaopen/ooz056.Peer-Reviewed Original ResearchUnderstanding the patient perspective of epilepsy treatment through text mining of online patient support groups.
He K, Hong N, Lapalme-Remis S, Lan Y, Huang M, Li C, Yao L. Understanding the patient perspective of epilepsy treatment through text mining of online patient support groups. Epilepsy Behav 2019, 94: 65-71. PMID: 30893617, DOI: 10.1016/j.yebeh.2019.02.002.Peer-Reviewed Original ResearchADEpedia-on-OHDSI: A next generation pharmacovigilance signal detection platform using the OHDSI common data model.
Yu Y, Ruddy KJ, Hong N, Tsuji S, Wen A, Shah ND, Jiang G. ADEpedia-on-OHDSI: A next generation pharmacovigilance signal detection platform using the OHDSI common data model. J Biomed Inform 2019, 91: 103119. PMID: 30738946, DOI: 10.1016/j.jbi.2019.103119.Peer-Reviewed Original Research
2018
Automated Population of an i2b2 Clinical Data Warehouse using FHIR.
Solbrig HR, Hong N, Murphy SN, Jiang G. Automated Population of an i2b2 Clinical Data Warehouse using FHIR. AMIA Annu Symp Proc 2018, 2018: 979-988. PMID: 30815141.Peer-Reviewed Original ResearchStandardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP.
Hong N, Wen A, Mojarad MR, Sohn S, Liu H, Jiang G. Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP. AMIA Annu Symp Proc 2018, 2018: 574-583. PMID: 30815098.Peer-Reviewed Original ResearchIntegrating Structured and Unstructured EHR Data Using an FHIR-based Type System: A Case Study with Medication Data.
Hong N, Wen A, Shen F, Sohn S, Liu S, Liu H, Jiang G. Integrating Structured and Unstructured EHR Data Using an FHIR-based Type System: A Case Study with Medication Data. AMIA Jt Summits Transl Sci Proc 2018, 2017: 74-83. PMID: 29888045.Peer-Reviewed Original Research
2016
A computational framework for converting textual clinical diagnostic criteria into the quality data model.
Hong N, Li D, Yu Y, Xiu Q, Liu H, Jiang G. A computational framework for converting textual clinical diagnostic criteria into the quality data model. J Biomed Inform 2016, 63: 11-21. PMID: 27444185, DOI: 10.1016/j.jbi.2016.07.016.Peer-Reviewed Original Research