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 *

248 related articles for article (PubMed ID: 34389139)

  • 1. Artificial Intelligence in Acute Kidney Injury: From Static to Dynamic Models.
    Mistry NS; Koyner JL
    Adv Chronic Kidney Dis; 2021 Jan; 28(1):74-82. PubMed ID: 34389139
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Artificial Intelligence in Acute Kidney Injury Prediction.
    Bajaj T; Koyner JL
    Adv Chronic Kidney Dis; 2022 Sep; 29(5):450-460. PubMed ID: 36253028
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions.
    Raina R; Nada A; Shah R; Aly H; Kadatane S; Abitbol C; Aggarwal M; Koyner J; Neyra J; Sethi SK
    Pediatr Nephrol; 2024 Aug; 39(8):2309-2324. PubMed ID: 37889281
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury.
    Howarth M; Bhatt M; Benterud E; Wolska A; Minty E; Choi KY; Devrome A; Harrison TG; Baylis B; Dixon E; Datta I; Pannu N; James MT
    BMC Med Inform Decis Mak; 2020 Nov; 20(1):287. PubMed ID: 33148237
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Electronic health record identification of nephrotoxin exposure and associated acute kidney injury.
    Goldstein SL; Kirkendall E; Nguyen H; Schaffzin JK; Bucuvalas J; Bracke T; Seid M; Ashby M; Foertmeyer N; Brunner L; Lesko A; Barclay C; Lannon C; Muething S
    Pediatrics; 2013 Sep; 132(3):e756-67. PubMed ID: 23940245
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Artificial Intelligence and Machine Learning in Perioperative Acute Kidney Injury.
    Takkavatakarn K; Hofer IS
    Adv Kidney Dis Health; 2023 Jan; 30(1):53-60. PubMed ID: 36723283
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Acute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support.
    Wilson FP; Greenberg JH
    Nephron; 2018; 140(2):116-119. PubMed ID: 30071528
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Artificial Intelligence in Acute Kidney Injury Risk Prediction.
    Gameiro J; Branco T; Lopes JA
    J Clin Med; 2020 Mar; 9(3):. PubMed ID: 32138284
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Artificial intelligence and acute kidney injury].
    Perschinka F; Peer A; Joannidis M
    Med Klin Intensivmed Notfmed; 2024 Apr; 119(3):199-207. PubMed ID: 38396124
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Electronic Medical Record-Based Predictive Model for Acute Kidney Injury in an Acute Care Hospital.
    LaszczyƄska O; Severo M; Azevedo A
    Stud Health Technol Inform; 2016; 228():810-2. PubMed ID: 27577501
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Artificial intelligence to guide management of acute kidney injury in the ICU: a narrative review.
    De Vlieger G; Kashani K; Meyfroidt G
    Curr Opin Crit Care; 2020 Dec; 26(6):563-573. PubMed ID: 33027147
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study.
    Chua HR; Zheng K; Vathsala A; Ngiam KY; Yap HK; Lu L; Tiong HY; Mukhopadhyay A; MacLaren G; Lim SL; Akalya K; Ooi BC
    J Med Internet Res; 2021 Dec; 23(12):e30805. PubMed ID: 34951595
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Impact of e-alert for detection of acute kidney injury on processes of care and outcomes: protocol for a systematic review and meta-analysis.
    Lachance P; Villeneuve PM; Wilson FP; Selby NM; Featherstone R; Rewa O; Bagshaw SM
    BMJ Open; 2016 May; 6(5):e011152. PubMed ID: 27150187
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Role of artificial intelligence in the diagnosis and management of kidney disease: applications to chronic kidney disease and acute kidney injury.
    Tangri N; Ferguson TW
    Curr Opin Nephrol Hypertens; 2022 May; 31(3):283-287. PubMed ID: 35190505
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Artificial Intelligence in Heart Failure and Acute Kidney Injury: Emerging Concepts and Controversial Dimensions.
    Cheungpasitporn W; Thongprayoon C; Kashani KB
    Cardiorenal Med; 2024; 14(1):147-159. PubMed ID: 38350433
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit.
    Gottlieb ER; Samuel M; Bonventre JV; Celi LA; Mattie H
    Adv Chronic Kidney Dis; 2022 Sep; 29(5):431-438. PubMed ID: 36253026
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.