BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

92 related articles for article (PubMed ID: 28714447)

  • 1. Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm.
    Brennan CW; Meng F; Meterko MM; D'Avolio LW
    J Nurs Meas; 2016 Dec; 24(3):419-427. PubMed ID: 28714447
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting patient acuity from electronic patient records.
    Kontio E; Airola A; Pahikkala T; Lundgren-Laine H; Junttila K; Korvenranta H; Salakoski T; Salanterä S
    J Biomed Inform; 2014 Oct; 51():35-40. PubMed ID: 24726853
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing.
    Ivanov O; Wolf L; Brecher D; Lewis E; Masek K; Montgomery K; Andrieiev Y; McLaughlin M; Liu S; Dunne R; Klauer K; Reilly C
    J Emerg Nurs; 2021 Mar; 47(2):265-278.e7. PubMed ID: 33358394
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
    Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
    J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Developing a caseload classification tool for community nursing.
    Chapman H; Kilner M; Matthews R; White A; Thompson A; Fowler-Davis S; Farndon L
    Br J Community Nurs; 2017 Apr; 22(4):192-196. PubMed ID: 28414537
    [TBL] [Abstract][Full Text] [Related]  

  • 6. From evidence to practice: developing an outpatient acuity-based staffing model.
    Vortherms J; Spoden B; Wilcken J
    Clin J Oncol Nurs; 2015 Jun; 19(3):332-7. PubMed ID: 26000583
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automating classification of free-text electronic health records for epidemiological studies.
    Schuemie MJ; Sen E; 't Jong GW; van Soest EM; Sturkenboom MC; Kors JA
    Pharmacoepidemiol Drug Saf; 2012 Jun; 21(6):651-8. PubMed ID: 22271492
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Personalized and automated remote monitoring of atrial fibrillation.
    Rosier A; Mabo P; Temal L; Van Hille P; Dameron O; Deléger L; Grouin C; Zweigenbaum P; Jacques J; Chazard E; Laporte L; Henry C; Burgun A
    Europace; 2016 Mar; 18(3):347-52. PubMed ID: 26487670
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning.
    Wang Z; Shah AD; Tate AR; Denaxas S; Shawe-Taylor J; Hemingway H
    PLoS One; 2012; 7(1):e30412. PubMed ID: 22276193
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Inter-Rater Reliability of Unstructured Text Labeling: Artificially vs. Naturally Intelligent Approaches.
    Danilov G; Kosyrkova A; Shults M; Melchenko S; Tsukanova T; Shifrin M; Potapov A
    Stud Health Technol Inform; 2021 May; 281():118-122. PubMed ID: 34042717
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Using workload measurement tools in diverse care contexts: the experience of staff in mental health and learning disability inpatient settings.
    Fanneran T; Brimblecombe N; Bradley E; Gregory S
    J Psychiatr Ment Health Nurs; 2015 Dec; 22(10):764-72. PubMed ID: 26608674
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Artificial Intelligence in Medical Practice: The Question to the Answer?
    Miller DD; Brown EW
    Am J Med; 2018 Feb; 131(2):129-133. PubMed ID: 29126825
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Using natural language processing and machine learning to identify gout flares from electronic clinical notes.
    Zheng C; Rashid N; Wu YL; Koblick R; Lin AT; Levy GD; Cheetham TC
    Arthritis Care Res (Hoboken); 2014 Nov; 66(11):1740-8. PubMed ID: 24664671
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A machine learning-based framework to identify type 2 diabetes through electronic health records.
    Zheng T; Xie W; Xu L; He X; Zhang Y; You M; Yang G; Chen Y
    Int J Med Inform; 2017 Jan; 97():120-127. PubMed ID: 27919371
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Cognitive Machine-Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis From Restrictive Cardiomyopathy.
    Sengupta PP; Huang YM; Bansal M; Ashrafi A; Fisher M; Shameer K; Gall W; Dudley JT
    Circ Cardiovasc Imaging; 2016 Jun; 9(6):. PubMed ID: 27266599
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Natural Language Processing for Real-Time Catheter-Associated Urinary Tract Infection Surveillance: Results of a Pilot Implementation Trial.
    Branch-Elliman W; Strymish J; Kudesia V; Rosen AK; Gupta K
    Infect Control Hosp Epidemiol; 2015 Sep; 36(9):1004-10. PubMed ID: 26022228
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Medical text representations for inductive learning.
    Wilcox A; Hripcsak G
    Proc AMIA Symp; 2000; ():923-7. PubMed ID: 11080019
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Does daily nurse staffing match ward workload variability? Three hospitals' experiences.
    Gabbay U; Bukchin M
    Int J Health Care Qual Assur; 2009; 22(6):625-41. PubMed ID: 19957423
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Identifying Outliers in Data from Patient Record.
    Baumberger D; Buergin R
    Stud Health Technol Inform; 2016; 225():402-6. PubMed ID: 27332231
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Staffing based on evidence: can health information technology make it possible?
    Harper EM
    Nurs Econ; 2012; 30(5):262-7, 281. PubMed ID: 23198608
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.