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 *

169 related articles for article (PubMed ID: 27577501)

  • 21. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
    Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
    Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
    [TBL] [Abstract][Full Text] [Related]  

  • 22. AKI in hospitalized children: comparing the pRIFLE, AKIN, and KDIGO definitions.
    Sutherland SM; Byrnes JJ; Kothari M; Longhurst CA; Dutta S; Garcia P; Goldstein SL
    Clin J Am Soc Nephrol; 2015 Apr; 10(4):554-61. PubMed ID: 25649155
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Opportunities in digital health and electronic health records for acute kidney injury care.
    Selby NM; Pannu N
    Curr Opin Crit Care; 2022 Dec; 28(6):605-612. PubMed ID: 35942677
    [TBL] [Abstract][Full Text] [Related]  

  • 24. The incidence of pediatric acute kidney injury is increased when identified by a change in a creatinine-based electronic alert.
    Holmes J; Roberts G; May K; Tyerman K; Geen J; Williams JD; Phillips AO;
    Kidney Int; 2017 Aug; 92(2):432-439. PubMed ID: 28483379
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Acute Kidney Injury and Information Technology.
    Küllmar M; Zarbock A
    Contrib Nephrol; 2018; 193():81-88. PubMed ID: 29393136
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Comparing Machine Learning Algorithms for Predicting Acute Kidney Injury.
    Parreco J; Soe-Lin H; Parks JJ; Byerly S; Chatoor M; Buicko JL; Namias N; Rattan R
    Am Surg; 2019 Jul; 85(7):725-729. PubMed ID: 31405416
    [TBL] [Abstract][Full Text] [Related]  

  • 27. eResearch in acute kidney injury: a primer for electronic health record research.
    Joyce EL; DeAlmeida DR; Fuhrman DY; Priyanka P; Kellum JA
    Nephrol Dial Transplant; 2019 Mar; 34(3):401-407. PubMed ID: 29617846
    [TBL] [Abstract][Full Text] [Related]  

  • 28. The Use of Automated Electronic Alerts in Studying Short-Term Outcomes Associated with Community-Acquired Acute Kidney Injury.
    Hazara AM; Elgaali M; Naudeer S; Holding S; Bhandari S
    Nephron; 2017; 135(3):181-188. PubMed ID: 28030861
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Sniffing out acute kidney injury in the ICU: do we have the tools?
    Kashani K; Herasevich V
    Curr Opin Crit Care; 2013 Dec; 19(6):531-6. PubMed ID: 24141395
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Electronic Data Systems and Acute Kidney Injury.
    Cheungpasitporn W; Kashani K
    Contrib Nephrol; 2016; 187():73-83. PubMed ID: 26882100
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Using a linked database for epidemiology across the primary and secondary care divide: acute kidney injury.
    Johnson M; Hounkpatin H; Fraser S; Culliford D; Uniacke M; Roderick P
    BMC Med Inform Decis Mak; 2017 Jul; 17(1):106. PubMed ID: 28693548
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Incidence and diagnosis of Acute kidney injury in hospitalized adult patients: a retrospective observational study in a tertiary teaching Hospital in Southeast China.
    Cheng X; Wu B; Liu Y; Mao H; Xing C
    BMC Nephrol; 2017 Jun; 18(1):203. PubMed ID: 28646870
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Early prediction of acquiring acute kidney injury for older inpatients using most effective laboratory test results.
    Chen YS; Chou CY; Chen ALP
    BMC Med Inform Decis Mak; 2020 Feb; 20(1):36. PubMed ID: 32079533
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Development and performance of electronic acute kidney injury triggers to identify pediatric patients at risk for nephrotoxic medication-associated harm.
    Kirkendall ES; Spires WL; Mottes TA; Schaffzin JK; Barclay C; Goldstein SL
    Appl Clin Inform; 2014; 5(2):313-33. PubMed ID: 25024752
    [TBL] [Abstract][Full Text] [Related]  

  • 35. The Role of Risk Prediction Models in Prevention and Management of AKI.
    Hodgson LE; Selby N; Huang TM; Forni LG
    Semin Nephrol; 2019 Sep; 39(5):421-430. PubMed ID: 31514906
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Seasonality of acute kidney injury phenotypes in England: an unsupervised machine learning classification study of electronic health records.
    Bolt H; Suffel A; Matthewman J; Sandmann F; Tomlinson L; Eggo R
    BMC Nephrol; 2023 Aug; 24(1):234. PubMed ID: 37558976
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Derivation and validation of a prediction score for acute kidney injury in patients hospitalized with acute heart failure in a Chinese cohort.
    Wang YN; Cheng H; Yue T; Chen YP
    Nephrology (Carlton); 2013 Jul; 18(7):489-96. PubMed ID: 23607443
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Predicting acute kidney injury at hospital re-entry using high-dimensional electronic health record data.
    Weisenthal SJ; Quill C; Farooq S; Kautz H; Zand MS
    PLoS One; 2018; 13(11):e0204920. PubMed ID: 30458044
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Risk factors for the prognosis of acute kidney injury under the Acute Kidney Injury Network definition: a retrospective, multicenter study in critically ill patients.
    Zhou J; Yang L; Zhang K; Liu Y; Fu P
    Nephrology (Carlton); 2012 May; 17(4):330-7. PubMed ID: 22309622
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Dialysis requirement, long-term major adverse cardiovascular events (MACE) and all-cause mortality in hospital acquired acute kidney injury (AKI): a propensity-matched cohort study.
    Omotoso BA; Abdel-Rahman EM; Xin W; Ma JZ; Scully KW; Arogundade FA; Balogun RA
    J Nephrol; 2016 Dec; 29(6):847-855. PubMed ID: 27307250
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.