These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

143 related articles for article (PubMed ID: 33338667)

  • 1. A prediction and interpretation framework of acute kidney injury in critical care.
    Gong K; Lee HK; Yu K; Xie X; Li J
    J Biomed Inform; 2021 Jan; 113():103653. PubMed ID: 33338667
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Utilizing imbalanced electronic health records to predict acute kidney injury by ensemble learning and time series model.
    Wang Y; Wei Y; Yang H; Li J; Zhou Y; Wu Q
    BMC Med Inform Decis Mak; 2020 Sep; 20(1):238. PubMed ID: 32957977
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Interpretable and Continuous Prediction of Acute Kidney Injury in the Intensive Care.
    Vagliano I; Lvova O; Schut MC
    Stud Health Technol Inform; 2021 May; 281():103-107. PubMed ID: 34042714
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care.
    Dong J; Feng T; Thapa-Chhetry B; Cho BG; Shum T; Inwald DP; Newth CJL; Vaidya VU
    Crit Care; 2021 Aug; 25(1):288. PubMed ID: 34376222
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.
    Hsu CN; Liu CL; Tain YL; Kuo CY; Lin YC
    J Med Internet Res; 2020 Aug; 22(8):e16903. PubMed ID: 32749223
    [TBL] [Abstract][Full Text] [Related]  

  • 6. [Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].
    Tang CQ; Li JQ; Xu DY; Liu XB; Hou WJ; Lyu KY; Xiao SC; Xia ZF
    Zhonghua Shao Shang Za Zhi; 2018 Jun; 34(6):343-348. PubMed ID: 29961290
    [No Abstract]   [Full Text] [Related]  

  • 7. Prediction and detection models for acute kidney injury in hospitalized older adults.
    Kate RJ; Perez RM; Mazumdar D; Pasupathy KS; Nilakantan V
    BMC Med Inform Decis Mak; 2016 Mar; 16():39. PubMed ID: 27025458
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A continual prediction model for inpatient acute kidney injury.
    Kate RJ; Pearce N; Mazumdar D; Nilakantan V
    Comput Biol Med; 2020 Jan; 116():103580. PubMed ID: 32001013
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development and Comparative Analysis of an Early Prediction Model for Acute Kidney Injury within 72-Hours Post-ICU Admission Using Evidence from the MIMIC-III Database.
    Luo Y; Ye W; Sun Y; Bao H; Liu H
    Discov Med; 2023 Aug; 35(177):623-631. PubMed ID: 37553314
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning, Clinical Notes and Knowledge Graphs for Early Prediction of Acute Kidney Injury in the Intensive Care.
    Vagliano I; Hsu WH; Schut MC
    Stud Health Technol Inform; 2022 Jan; 289():329-332. PubMed ID: 35062159
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease.
    Zhang X; Chen S; Lai K; Chen Z; Wan J; Xu Y
    Ren Fail; 2022 Dec; 44(1):43-53. PubMed ID: 35166177
    [TBL] [Abstract][Full Text] [Related]  

  • 12. External Validation and Transportability of Models to Predict Acute Kidney Injury in the Intensive Care Unit.
    Vagliano I; Byrne Salsas C; Wünn T; Schut MC
    Stud Health Technol Inform; 2022 Jun; 295():148-151. PubMed ID: 35773829
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Including urinary output to define AKI enhances the performance of machine learning models to predict AKI at admission.
    Schwager E; Lanius S; Ghosh E; Eshelman L; Pasupathy KS; Barreto EF; Kashani K
    J Crit Care; 2021 Apr; 62():283-288. PubMed ID: 33508763
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor.
    Flechet M; Falini S; Bonetti C; Güiza F; Schetz M; Van den Berghe G; Meyfroidt G
    Crit Care; 2019 Aug; 23(1):282. PubMed ID: 31420056
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model.
    Lin K; Hu Y; Kong G
    Int J Med Inform; 2019 May; 125():55-61. PubMed ID: 30914181
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Stratified Mortality Prediction of Patients with Acute Kidney Injury in Critical Care.
    Xu Z; Luo Y; Adekkanattu P; Ancker JS; Jiang G; Kiefer RC; Pacheco JA; Rasmussen LV; Pathak J; Wang F
    Stud Health Technol Inform; 2019 Aug; 264():462-466. PubMed ID: 31437966
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Urinary biomarker incorporation into the renal angina index early in intensive care unit admission optimizes acute kidney injury prediction in critically ill children: a prospective cohort study.
    Menon S; Goldstein SL; Mottes T; Fei L; Kaddourah A; Terrell T; Arnold P; Bennett MR; Basu RK
    Nephrol Dial Transplant; 2016 Apr; 31(4):586-94. PubMed ID: 26908772
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.
    Zhang Z; Ho KM; Hong Y
    Crit Care; 2019 Apr; 23(1):112. PubMed ID: 30961662
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Risk Prediction Models for Acute Kidney Injury in Critically Ill Patients: Opus in Progressu.
    Neyra JA; Leaf DE
    Nephron; 2018; 140(2):99-104. PubMed ID: 29852504
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Biomarker Predictors of Adverse Acute Kidney Injury Outcomes in Critically Ill Patients: The Dublin Acute Biomarker Group Evaluation Study.
    McMahon BA; Galligan M; Redahan L; Martin T; Meaney E; Cotter EJ; Murphy N; Hannon C; Doran P; Marsh B; Nichol A; Murray PT
    Am J Nephrol; 2019; 50(1):19-28. PubMed ID: 31203271
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.