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 *

144 related articles for article (PubMed ID: 37827476)

  • 61. Early Detection of Septic Shock Onset Using Interpretable Machine Learners.
    Misra D; Avula V; Wolk DM; Farag HA; Li J; Mehta YB; Sandhu R; Karunakaran B; Kethireddy S; Zand R; Abedi V
    J Clin Med; 2021 Jan; 10(2):. PubMed ID: 33467539
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Significance of platelets in the early warning of new-onset AKI in the ICU by using supervise learning: a retrospective analysis.
    Pan P; Liu Y; Xie F; Duan Z; Li L; Gu H; Xie L; Lu X; Su L
    Ren Fail; 2023 Dec; 45(1):2194433. PubMed ID: 37013397
    [TBL] [Abstract][Full Text] [Related]  

  • 63. Using EHR audit trail logs to analyze clinical workflow: A case study from community-based ambulatory clinics.
    Wu DTY; Smart N; Ciemins EL; Lanham HJ; Lindberg C; Zheng K
    AMIA Annu Symp Proc; 2017; 2017():1820-1827. PubMed ID: 29854253
    [TBL] [Abstract][Full Text] [Related]  

  • 64. 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]  

  • 65. Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records.
    He J; Hu Y; Zhang X; Wu L; Waitman LR; Liu M
    JAMIA Open; 2019 Apr; 2(1):115-122. PubMed ID: 30976758
    [TBL] [Abstract][Full Text] [Related]  

  • 66. Development of an automated phenotyping algorithm for hepatorenal syndrome.
    Koola JD; Davis SE; Al-Nimri O; Parr SK; Fabbri D; Malin BA; Ho SB; Matheny ME
    J Biomed Inform; 2018 Apr; 80():87-95. PubMed ID: 29530803
    [TBL] [Abstract][Full Text] [Related]  

  • 67. Supervised machine learning-based prediction for in-hospital pressure injury development using electronic health records: A retrospective observational cohort study in a university hospital in Japan.
    Nakagami G; Yokota S; Kitamura A; Takahashi T; Morita K; Noguchi H; Ohe K; Sanada H
    Int J Nurs Stud; 2021 Jul; 119():103932. PubMed ID: 33975074
    [TBL] [Abstract][Full Text] [Related]  

  • 68. Prediction of Long-Term Stroke Recurrence Using Machine Learning Models.
    Abedi V; Avula V; Chaudhary D; Shahjouei S; Khan A; Griessenauer CJ; Li J; Zand R
    J Clin Med; 2021 Mar; 10(6):. PubMed ID: 33804724
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Effect of a Pharmacist-Driven Monitoring Program and Electronic Health Record on Bleeding Log Completeness and Documentation.
    Shay B; Kennerly-Shah J; Neidecker M; Beatty S; Witkoff L; Brown N; Kraut E
    J Manag Care Spec Pharm; 2018 Oct; 24(10):1034-1039. PubMed ID: 30247104
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.
    Jiang S; Lam BD; Agrawal M; Shen S; Kurtzman N; Horng S; Karger DR; Sontag D
    J Am Med Inform Assoc; 2024 Jun; 31(7):1578-1582. PubMed ID: 38700253
    [TBL] [Abstract][Full Text] [Related]  

  • 71. A guide to mitigating audit log-related risk in medical professional liability cases.
    Sittig DF; Wright A
    J Healthc Risk Manag; 2023 Oct; 43(2):37-47. PubMed ID: 37486791
    [TBL] [Abstract][Full Text] [Related]  

  • 72. Development of a Prediction Model of Early Acute Kidney Injury in Critically Ill Children Using Electronic Health Record Data.
    Sanchez-Pinto LN; Khemani RG
    Pediatr Crit Care Med; 2016 Jun; 17(6):508-15. PubMed ID: 27124567
    [TBL] [Abstract][Full Text] [Related]  

  • 73. Changing relative risk of clinical factors for hospital-acquired acute kidney injury across age groups: a retrospective cohort study.
    Wu L; Hu Y; Zhang X; Chen W; Yu ASL; Kellum JA; Waitman LR; Liu M
    BMC Nephrol; 2020 Aug; 21(1):321. PubMed ID: 32741377
    [TBL] [Abstract][Full Text] [Related]  

  • 74. National Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury.
    Cronin RM; VanHouten JP; Siew ED; Eden SK; Fihn SD; Nielson CD; Peterson JF; Baker CR; Ikizler TA; Speroff T; Matheny ME
    J Am Med Inform Assoc; 2015 Sep; 22(5):1054-71. PubMed ID: 26104740
    [TBL] [Abstract][Full Text] [Related]  

  • 75. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.
    Huang C; Murugiah K; Mahajan S; Li SX; Dhruva SS; Haimovich JS; Wang Y; Schulz WL; Testani JM; Wilson FP; Mena CI; Masoudi FA; Rumsfeld JS; Spertus JA; Mortazavi BJ; Krumholz HM
    PLoS Med; 2018 Nov; 15(11):e1002703. PubMed ID: 30481186
    [TBL] [Abstract][Full Text] [Related]  

  • 76. Machine learning prediction of postoperative major adverse cardiovascular events in geriatric patients: a prospective cohort study.
    Peng X; Zhu T; Wang T; Wang F; Li K; Hao X
    BMC Anesthesiol; 2022 Sep; 22(1):284. PubMed ID: 36088288
    [TBL] [Abstract][Full Text] [Related]  

  • 77. Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements.
    Zimmerman LP; Reyfman PA; Smith ADR; Zeng Z; Kho A; Sanchez-Pinto LN; Luo Y
    BMC Med Inform Decis Mak; 2019 Jan; 19(Suppl 1):16. PubMed ID: 30700291
    [TBL] [Abstract][Full Text] [Related]  

  • 78. Machine learning models to detect and predict patient safety events using electronic health records: A systematic review.
    Deimazar G; Sheikhtaheri A
    Int J Med Inform; 2023 Dec; 180():105246. PubMed ID: 37837710
    [TBL] [Abstract][Full Text] [Related]  

  • 79. Conceptual considerations for using EHR-based activity logs to measure clinician burnout and its effects.
    Kannampallil T; Abraham J; Lou SS; Payne PRO
    J Am Med Inform Assoc; 2021 Apr; 28(5):1032-1037. PubMed ID: 33355360
    [TBL] [Abstract][Full Text] [Related]  

  • 80.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

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