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 *

218 related articles for article (PubMed ID: 33959271)

  • 1. Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning.
    Shawwa K; Ghosh E; Lanius S; Schwager E; Eshelman L; Kashani KB
    Clin Kidney J; 2021 May; 14(5):1428-1435. PubMed ID: 33959271
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Machine Learning Algorithm Predicting Acute Kidney Injury in Intensive Care Unit Patients (NAVOY Acute Kidney Injury): Proof-of-Concept Study.
    Persson I; Grünwald A; Morvan L; Becedas D; Arlbrandt M
    JMIR Form Res; 2023 Dec; 7():e45979. PubMed ID: 38096015
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. [Incidence and mortality risk factors of acute kidney injury in critical ill pregnancies: a single center retrospective analysis].
    Ding M; Luan L; Zhang J; Jiang J; Qie G; Sha J; Zhu W; Zeng J; Chu Y
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2019 Dec; 31(12):1506-1511. PubMed ID: 32029038
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].
    Lin K; Xie JQ; Hu YH; Kong GL
    Beijing Da Xue Xue Bao Yi Xue Ban; 2018 Apr; 50(2):239-244. PubMed ID: 29643521
    [TBL] [Abstract][Full Text] [Related]  

  • 6. [Construction and validation of a decision tree based on biomarkers for predicting severe acute kidney injury in critically ill patients].
    Chi R; Liang M; Zou Q; Li C; Zhou H; Jian Z
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2020 Jun; 32(6):721-725. PubMed ID: 32684220
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Internal and external validation of machine learning-assisted prediction models for mechanical ventilation-associated severe acute kidney injury.
    Huang S; Teng Y; Du J; Zhou X; Duan F; Feng C
    Aust Crit Care; 2023 Jul; 36(4):604-612. PubMed ID: 35842332
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of Acute Kidney Injury in Intracerebral Hemorrhage Patients Using Machine Learning.
    She S; Shen Y; Luo K; Zhang X; Luo C
    Neuropsychiatr Dis Treat; 2023; 19():2765-2773. PubMed ID: 38106359
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Acute kidney injury risk prediction score for critically-ill surgical patients.
    Trongtrakul K; Patumanond J; Kongsayreepong S; Morakul S; Pipanmekaporn T; Akaraborworn O; Poopipatpab S
    BMC Anesthesiol; 2020 Jun; 20(1):140. PubMed ID: 32493268
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction of acute kidney injury in ICU with gradient boosting decision tree algorithms.
    Gao W; Wang J; Zhou L; Luo Q; Lao Y; Lyu H; Guo S
    Comput Biol Med; 2022 Jan; 140():105097. PubMed ID: 34864304
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting acute kidney injury risk in acute myocardial infarction patients: An artificial intelligence model using medical information mart for intensive care databases.
    Cai D; Xiao T; Zou A; Mao L; Chi B; Wang Y; Wang Q; Ji Y; Sun L
    Front Cardiovasc Med; 2022; 9():964894. PubMed ID: 36158815
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning model for predicting acute kidney injury progression in critically ill patients.
    Wei C; Zhang L; Feng Y; Ma A; Kang Y
    BMC Med Inform Decis Mak; 2022 Jan; 22(1):17. PubMed ID: 35045840
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A risk prediction score for acute kidney injury in the intensive care unit.
    Malhotra R; Kashani KB; Macedo E; Kim J; Bouchard J; Wynn S; Li G; Ohno-Machado L; Mehta R
    Nephrol Dial Transplant; 2017 May; 32(5):814-822. PubMed ID: 28402551
    [TBL] [Abstract][Full Text] [Related]  

  • 14. [Relationship between postoperative immediate serum albumin level and postoperative acute kidney injury after major abdominal surgery in critically ill patients].
    Li W; Li N; Li S
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2021 Aug; 33(8):955-961. PubMed ID: 34590563
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of persistent acute kidney injury in postoperative intensive care unit patients using integrated machine learning: a retrospective cohort study.
    Jiang X; Hu Y; Guo S; Du C; Cheng X
    Sci Rep; 2022 Oct; 12(1):17134. PubMed ID: 36224308
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Subclinical acute kidney injury is associated with adverse outcomes in critically ill neonates and children.
    Fang F; Hu X; Dai X; Wang S; Bai Z; Chen J; Pan J; Li X; Wang J; Li Y
    Crit Care; 2018 Oct; 22(1):256. PubMed ID: 30305134
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of acute kidney injury in patients with femoral neck fracture utilizing machine learning.
    Liu J; Xu L; Zhu E; Han C; Ai Z
    Front Surg; 2022; 9():928750. PubMed ID: 35959132
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. A Machine Learning-Based Algorithm for the Prediction of Intensive Care Unit Delirium (PRIDE): Retrospective Study.
    Hur S; Ko RE; Yoo J; Ha J; Cha WC; Chung CR
    JMIR Med Inform; 2021 Jul; 9(7):e23401. PubMed ID: 34309567
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Development of acute kidney injury prognostic model for critically ill patients based on MIMIC-III database].
    Li M; Yang H; Yang W; Wei B; Zhang Y; Xie R; Chu P
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2021 Aug; 33(8):949-954. PubMed ID: 34590562
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.