BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

163 related articles for article (PubMed ID: 24786209)

  • 1. N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit.
    Marafino BJ; Davies JM; Bardach NS; Dean ML; Dudley RA
    J Am Med Inform Assoc; 2014; 21(5):871-5. PubMed ID: 24786209
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient and sparse feature selection for biomedical text classification via the elastic net: Application to ICU risk stratification from nursing notes.
    Marafino BJ; Boscardin WJ; Dudley RA
    J Biomed Inform; 2015 Apr; 54():114-20. PubMed ID: 25700665
    [TBL] [Abstract][Full Text] [Related]  

  • 3. TGRA-P: Task-driven model predicts 90-day mortality from ICU clinical notes on mechanical ventilation.
    Zou B; Ding Y; Li J; Yu B; Kui X
    Comput Methods Programs Biomed; 2023 Dec; 242():107783. PubMed ID: 37716220
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.
    Azzolina D; Bressan S; Lorenzoni G; Baldan GA; Bartolotta P; Scognamiglio F; Francavilla A; Lanera C; Da Dalt L; Gregori D
    JMIR Public Health Surveill; 2023 Jul; 9():e44467. PubMed ID: 37436799
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-assisted lip diagnosis on Traditional Chinese Medicine using multi-class support vector machines.
    Li F; Zhao C; Xia Z; Wang Y; Zhou X; Li GZ
    BMC Complement Altern Med; 2012 Aug; 12():127. PubMed ID: 22898352
    [TBL] [Abstract][Full Text] [Related]  

  • 6. [Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].
    Lin K; Xie JQ; Hu YH; Kong GL
    Beijing Da Xue Xue Bao Yi Xue Ban; 2018 Apr; 50(2):239-244. PubMed ID: 29643521
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Optimal classification for the diagnosis of duchenne muscular dystrophy images using support vector machines.
    Zhang MH; Ma JS; Shen Y; Chen Y
    Int J Comput Assist Radiol Surg; 2016 Sep; 11(9):1755-63. PubMed ID: 26476638
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Use of a support vector machine for categorizing free-text notes: assessment of accuracy across two institutions.
    Wright A; McCoy AB; Henkin S; Kale A; Sittig DF
    J Am Med Inform Assoc; 2013; 20(5):887-90. PubMed ID: 23543111
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Learning regular expressions for clinical text classification.
    Bui DD; Zeng-Treitler Q
    J Am Med Inform Assoc; 2014; 21(5):850-7. PubMed ID: 24578357
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic figure classification in bioscience literature.
    Kim D; Ramesh BP; Yu H
    J Biomed Inform; 2011 Oct; 44(5):848-58. PubMed ID: 21645638
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automated Classification of Selected Data Elements from Free-text Diagnostic Reports for Clinical Research.
    Löpprich M; Krauss F; Ganzinger M; Senghas K; Riezler S; Knaup P
    Methods Inf Med; 2016 Aug; 55(4):373-80. PubMed ID: 27406024
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study.
    Maarseveen TD; Meinderink T; Reinders MJT; Knitza J; Huizinga TWJ; Kleyer A; Simon D; van den Akker EB; Knevel R
    JMIR Med Inform; 2020 Nov; 8(11):e23930. PubMed ID: 33252349
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Natural language processing and machine learning to enable automatic extraction and classification of patients' smoking status from electronic medical records.
    Caccamisi A; Jørgensen L; Dalianis H; Rosenlund M
    Ups J Med Sci; 2020 Nov; 125(4):316-324. PubMed ID: 32696698
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Semi-supervised clinical text classification with Laplacian SVMs: an application to cancer case management.
    Garla V; Taylor C; Brandt C
    J Biomed Inform; 2013 Oct; 46(5):869-75. PubMed ID: 23845911
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Classification of electrocardiogram signals with support vector machines and particle swarm optimization.
    Melgani F; Bazi Y
    IEEE Trans Inf Technol Biomed; 2008 Sep; 12(5):667-77. PubMed ID: 18779082
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessing the similarity of surface linguistic features related to epilepsy across pediatric hospitals.
    Connolly B; Matykiewicz P; Bretonnel Cohen K; Standridge SM; Glauser TA; Dlugos DJ; Koh S; Tham E; Pestian J
    J Am Med Inform Assoc; 2014; 21(5):866-70. PubMed ID: 24692393
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Machine Learning decision-making tool for extubation in Intensive Care Unit patients.
    Fabregat A; Magret M; Ferré JA; Vernet A; Guasch N; Rodríguez A; Gómez J; Bodí M
    Comput Methods Programs Biomed; 2021 Mar; 200():105869. PubMed ID: 33250280
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: comparison to a Bayesian classifier.
    Chang Y; Lim J; Kim N; Seo JB; Lynch DA
    Med Phys; 2013 May; 40(5):051912. PubMed ID: 23635282
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries.
    Hong N; Wen A; Stone DJ; Tsuji S; Kingsbury PR; Rasmussen LV; Pacheco JA; Adekkanattu P; Wang F; Luo Y; Pathak J; Liu H; Jiang G
    J Biomed Inform; 2019 Nov; 99():103310. PubMed ID: 31622801
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A novel model to label delirium in an intensive care unit from clinician actions.
    Coombes CE; Coombes KR; Fareed N
    BMC Med Inform Decis Mak; 2021 Mar; 21(1):97. PubMed ID: 33750375
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.