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 *

142 related articles for article (PubMed ID: 33338667)

  • 41. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
    Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A
    Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Does Artificial Intelligence Make Clinical Decision Better? A Review of Artificial Intelligence and Machine Learning in Acute Kidney Injury Prediction.
    Lee TH; Chen JJ; Cheng CT; Chang CH
    Healthcare (Basel); 2021 Nov; 9(12):. PubMed ID: 34946388
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Predicting AKI in emergency admissions: an external validation study of the acute kidney injury prediction score (APS).
    Hodgson LE; Dimitrov BD; Roderick PJ; Venn R; Forni LG
    BMJ Open; 2017 Mar; 7(3):e013511. PubMed ID: 28274964
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Predictive value of plasma neutrophil gelatinase-associated lipocalin for acute kidney injury in intensive care unit patients after major non-cardiac surgery.
    Shum HP; Leung NY; Chang LL; Tam OY; Kwan AM; Chan KC; Yan WW; Chan TM
    Nephrology (Carlton); 2015 May; 20(5):375-82. PubMed ID: 25605005
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Acute kidney injury in an intensive care unit of a general hospital with emergency room specializing in trauma: an observational prospective study.
    Santos PR; Monteiro DL
    BMC Nephrol; 2015 Mar; 16():30. PubMed ID: 25885883
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Prediction and visualization of acute kidney injury in intensive care unit using one-dimensional convolutional neural networks based on routinely collected data.
    Sato N; Uchino E; Kojima R; Hiragi S; Yanagita M; Okuno Y
    Comput Methods Programs Biomed; 2021 Jul; 206():106129. PubMed ID: 34020177
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Electronic health records accurately predict renal replacement therapy in acute kidney injury.
    Low S; Vathsala A; Murali TM; Pang L; MacLaren G; Ng WY; Haroon S; Mukhopadhyay A; Lim SL; Tan BH; Lau T; Chua HR
    BMC Nephrol; 2019 Jan; 20(1):32. PubMed ID: 30704418
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational study.
    Bourdeaux C; Ghosh E; Atallah L; Palanisamy K; Patel P; Thomas M; Gould T; Warburton J; Rivers J; Hadfield J
    Crit Care; 2020 Nov; 24(1):656. PubMed ID: 33228770
    [TBL] [Abstract][Full Text] [Related]  

  • 49. The intensive care medicine agenda on acute kidney injury.
    Pickkers P; Ostermann M; Joannidis M; Zarbock A; Hoste E; Bellomo R; Prowle J; Darmon M; Bonventre JV; Forni L; Bagshaw SM; Schetz M
    Intensive Care Med; 2017 Sep; 43(9):1198-1209. PubMed ID: 28138736
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Using Machine Learning to Predict Acute Kidney Injury After Aortic Arch Surgery.
    Lei G; Wang G; Zhang C; Chen Y; Yang X
    J Cardiothorac Vasc Anesth; 2020 Dec; 34(12):3321-3328. PubMed ID: 32636105
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Characterizing the temporal changes in association between modifiable risk factors and acute kidney injury with multi-view analysis.
    Liu K; Yuan B; Zhang X; Chen W; Patel LP; Hu Y; Liu M
    Int J Med Inform; 2022 Jul; 163():104785. PubMed ID: 35504130
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Neutrophil gelatinase-associated lipocalin at ICU admission predicts for acute kidney injury in adult patients.
    de Geus HR; Bakker J; Lesaffre EM; le Noble JL
    Am J Respir Crit Care Med; 2011 Apr; 183(7):907-14. PubMed ID: 20935115
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Acute kidney injury diagnosis in Intensive Care Units: biomarkers or Information?
    Farias Filho FT; Malafaia MC; Martins ET
    J Bras Nefrol; 2017 Mar; 39(1):95-96. PubMed ID: 28355400
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Development and validation of quick Acute Kidney Injury-score (q-AKI) to predict acute kidney injury at admission to a multidisciplinary intensive care unit.
    Ferrari F; Puci MV; Ferraro OE; Romero-González G; Husain-Syed F; Rizo-Topete L; Senzolo M; Lorenzin A; Muraro E; Baracca A; Serrano-Soto M; Molano Triviño A; Coutinho Castro A; De Cal M; Corradi V; Brendolan A; Scarpa M; Carta MR; Giavarina D; Bonato R; Iotti GA; Ronco C
    PLoS One; 2019; 14(6):e0217424. PubMed ID: 31220087
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Early serum cystatin C-enhanced risk prediction for acute kidney injury post cardiac surgery: a prospective, observational, cohort study.
    Wang X; Lin X; Xie B; Huang R; Yan Y; Liu S; Zhu M; Lu R; Qian J; Ni Z; Xue S; Che M
    Biomarkers; 2020 Feb; 25(1):20-26. PubMed ID: 31686541
    [No Abstract]   [Full Text] [Related]  

  • 56. Evaluation of clinically available renal biomarkers in critically ill adults: a prospective multicenter observational study.
    Deng Y; Chi R; Chen S; Ye H; Yuan J; Wang L; Zhai Y; Gao L; Zhang D; Hu L; Lv B; Long Y; Sun C; Yang X; Zou X; Chen C
    Crit Care; 2017 Mar; 21(1):46. PubMed ID: 28264714
    [TBL] [Abstract][Full Text] [Related]  

  • 57. AKIpredictor, an online prognostic calculator for acute kidney injury in adult critically ill patients: development, validation and comparison to serum neutrophil gelatinase-associated lipocalin.
    Flechet M; Güiza F; Schetz M; Wouters P; Vanhorebeek I; Derese I; Gunst J; Spriet I; Casaer M; Van den Berghe G; Meyfroidt G
    Intensive Care Med; 2017 Jun; 43(6):764-773. PubMed ID: 28130688
    [TBL] [Abstract][Full Text] [Related]  

  • 58. [Application of a risk stratification-based model for prediction of acute kidney injury combined with hemoperfusion in patients with sepsis: a prospective, observational, pilot study].
    Feng F; Chen Y; Chen W; Yang H; Yang W; Du J; Li M
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2020 Jul; 32(7):814-818. PubMed ID: 32788015
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.
    Rashidi HH; Makley A; Palmieri TL; Albahra S; Loegering J; Fang L; Yamaguchi K; Gerlach T; Rodriquez D; Tran NK
    Arch Pathol Lab Med; 2021 Mar; 145(3):320-326. PubMed ID: 33635951
    [TBL] [Abstract][Full Text] [Related]  

  • 60. The incidence and associations of acute kidney injury in trauma patients admitted to critical care: A systematic review and meta-analysis.
    Haines RW; Fowler AJ; Kirwan CJ; Prowle JR
    J Trauma Acute Care Surg; 2019 Jan; 86(1):141-147. PubMed ID: 30358765
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.