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Found 14 results
Author Title [ Type(Desc)] Year
Filters: Author is Xu, Zhenxing  [Clear All Filters]
Journal Article
Xu Z, Su C, Xiao Y, Wang F.  2022.  Artificial intelligence for COVID-19: battling the pandemic with computational intelligence.. Intell Med. 2(1):13-29.
Rajendran S, Xu Z, Pan W, Ghosh A, Wang F.  2023.  Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care.. PLOS Digit Health. 2(3):e0000117.
Zhang H, Zang C, Xu Z, Zhang Y, Xu J, Bian J, Morozyuk D, Khullar D, Zhang Y, Nordvig AS et al..  2023.  Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.. Nat Med. 29(1):226-235.
Su C, Xu Z, Pathak J, Wang F.  2020.  Deep learning in mental health outcome research: a scoping review.. Transl Psychiatry. 10(1):116.
Brandt PS, Pacheco JA, Adekkanattu P, Sholle ET, Abedian S, Stone DJ, Knaack DM, Xu J, Xu Z, Peng Y et al..  2022.  Design and validation of a FHIR-based EHR-driven phenotyping toolbox.. J Am Med Inform Assoc. 29(9):1449-1460.
Varma JK, Zang C, Carton TW, Block JP, Khullar DJ, Zhang Y, Weiner MG, Rothman RL, Schenck EJ, Xu Z et al..  2023.  Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER Program.. medRxiv.
Zhang Y, Hu H, Fokaidis V, V CLewis, Xu J, Zang C, Xu Z, Wang F, Koropsak M, Bian J et al..  2023.  Identifying environmental risk factors for post-acute sequelae of SARS-CoV-2 infection: An EHR-based cohort study from the recover program.. Environ Adv. 11:100352.
Xu Z, Chou J, Zhang XSheryl, Luo Y, Isakova T, Adekkanattu P, Ancker JS, Jiang G, Kiefer RC, Pacheco JA et al..  2020.  Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks.. J Biomed Inform. 102:103361.
Mehta B, Goodman S, DiCarlo E, Jannat-Khah D, J Gibbons AB, Otero M, Donlin L, Pannellini T, Robinson WH, Sculco P et al..  2023.  Machine learning identification of thresholds to discriminate osteoarthritis and rheumatoid arthritis synovial inflammation.. Arthritis Res Ther. 25(1):31.
Kline A, Wang H, Li Y, Dennis S, Hutch M, Xu Z, Wang F, Cheng F, Luo Y.  2022.  Multimodal machine learning in precision health: A scoping review.. NPJ Digit Med. 5(1):171.
Adekkanattu P, Rasmussen LV, Pacheco JA, Kabariti J, Stone DJ, Yu Y, Jiang G, Luo Y, Brandt PS, Xu Z et al..  2023.  Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study.. Sci Rep. 13(1):294.
Khullar D, Zhang Y, Zang C, Xu Z, Wang F, Weiner MG, Carton TW, Rothman RL, Block JP, Kaushal R.  2023.  Racial/Ethnic Disparities in Post-acute Sequelae of SARS-CoV-2 Infection in New York: an EHR-Based Cohort Study from the RECOVER Program.. J Gen Intern Med. :1-10.
Zang C, Hou Y, Schenck E, Xu Z, Zhang Y, Xu J, Bian J, Morozyuk D, Khullar D, Nordvig A et al..  2023.  Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative.. Res Sq.
Xu Z, Mao C, Su C, Zhang H, Siempos I, Torres LK, Pan D, Luo Y, Schenck EJ, Wang F.  2022.  Sepsis subphenotyping based on organ dysfunction trajectory.. Crit Care. 26(1):197.