BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

194 related articles for article (PubMed ID: 32383971)

  • 1. Predicting Severe Chronic Obstructive Pulmonary Disease Exacerbations. Developing a Population Surveillance Approach with Administrative Data.
    Tavakoli H; Chen W; Sin DD; FitzGerald JM; Sadatsafavi M
    Ann Am Thorac Soc; 2020 Sep; 17(9):1069-1076. PubMed ID: 32383971
    [No Abstract]   [Full Text] [Related]  

  • 2. A clinical prediction model for hospitalized COPD exacerbations based on "treatable traits".
    Yii ACA; Loh CH; Tiew PY; Xu H; Taha AAM; Koh J; Tan J; Lapperre TS; Anzueto A; Tee AKH
    Int J Chron Obstruct Pulmon Dis; 2019; 14():719-728. PubMed ID: 30988606
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting Hospitalization Due to COPD Exacerbations in Swedish Primary Care Patients Using Machine Learning - Based on the ARCTIC Study.
    Ställberg B; Lisspers K; Larsson K; Janson C; Müller M; Łuczko M; Kjøller Bjerregaard B; Bacher G; Holzhauer B; Goyal P; Johansson G
    Int J Chron Obstruct Pulmon Dis; 2021; 16():677-688. PubMed ID: 33758504
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study.
    Zeng S; Arjomandi M; Tong Y; Liao ZC; Luo G
    J Med Internet Res; 2022 Jan; 24(1):e28953. PubMed ID: 34989686
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The Acute COPD Exacerbation Prediction Tool (ACCEPT): a modelling study.
    Adibi A; Sin DD; Safari A; Johnson KM; Aaron SD; FitzGerald JM; Sadatsafavi M
    Lancet Respir Med; 2020 Oct; 8(10):1013-1021. PubMed ID: 32178776
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and Validation of a Predictive Model to Identify Individuals Likely to Have Undiagnosed Chronic Obstructive Pulmonary Disease Using an Administrative Claims Database.
    Moretz C; Zhou Y; Dhamane AD; Burslem K; Saverno K; Jain G; Devercelli G; Kaila S; Ellis JJ; Hernandez G; Renda A
    J Manag Care Spec Pharm; 2015 Dec; 21(12):1149-59. PubMed ID: 26679964
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Validation of a New Risk Measure for Chronic Obstructive Pulmonary Disease Exacerbation Using Health Insurance Claims Data.
    Stanford RH; Nag A; Mapel DW; Lee TA; Rosiello R; Vekeman F; Gauthier-Loiselle M; Duh MS; Merrigan JF; Schatz M
    Ann Am Thorac Soc; 2016 Jul; 13(7):1067-75. PubMed ID: 27070274
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and validation of a model to predict the risk of exacerbations in chronic obstructive pulmonary disease.
    Bertens LC; Reitsma JB; Moons KG; van Mourik Y; Lammers JW; Broekhuizen BD; Hoes AW; Rutten FH
    Int J Chron Obstruct Pulmon Dis; 2013; 8():493-9. PubMed ID: 24143086
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using Machine Learning to Predict Likelihood and Cause of Readmission After Hospitalization for Chronic Obstructive Pulmonary Disease Exacerbation.
    Bonomo M; Hermsen MG; Kaskovich S; Hemmrich MJ; Rojas JC; Carey KA; Venable LR; Churpek MM; Press VG
    Int J Chron Obstruct Pulmon Dis; 2022; 17():2701-2709. PubMed ID: 36299799
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A score to predict short-term risk of COPD exacerbations (SCOPEX).
    Make BJ; Eriksson G; Calverley PM; Jenkins CR; Postma DS; Peterson S; Östlund O; Anzueto A
    Int J Chron Obstruct Pulmon Dis; 2015; 10():201-9. PubMed ID: 25670896
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study.
    Chaudhary MFA; Hoffman EA; Guo J; Comellas AP; Newell JD; Nagpal P; Fortis S; Christensen GE; Gerard SE; Pan Y; Wang D; Abtin F; Barjaktarevic IZ; Barr RG; Bhatt SP; Bodduluri S; Cooper CB; Gravens-Mueller L; Han MK; Kazerooni EA; Martinez FJ; Menchaca MG; Ortega VE; Iii RP; Schroeder JD; Woodruff PG; Reinhardt JM
    Lancet Digit Health; 2023 Feb; 5(2):e83-e92. PubMed ID: 36707189
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development and validation of a predictive model to identify patients at risk of severe COPD exacerbations using administrative claims data.
    Annavarapu S; Goldfarb S; Gelb M; Moretz C; Renda A; Kaila S
    Int J Chron Obstruct Pulmon Dis; 2018; 13():2121-2130. PubMed ID: 30022818
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study.
    Wu CT; Li GH; Huang CT; Cheng YC; Chen CH; Chien JY; Kuo PH; Kuo LC; Lai F
    JMIR Mhealth Uhealth; 2021 May; 9(5):e22591. PubMed ID: 33955840
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Developing and validating prediction models for severe exacerbations and readmissions in patients hospitalised for COPD exacerbation (SERCO) in China: a prospective observational study.
    Wang Y; He R; Ren X; Huang K; Lei J; Niu H; Li W; Dong F; Li B; Yang T; Wang C
    BMJ Open Respir Res; 2024 May; 11(1):. PubMed ID: 38719500
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Machine Learning-Based Prediction Models for 30-Day Readmission after Hospitalization for Chronic Obstructive Pulmonary Disease.
    Goto T; Jo T; Matsui H; Fushimi K; Hayashi H; Yasunaga H
    COPD; 2019 Dec; 16(5-6):338-343. PubMed ID: 31709851
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning-based prediction of in-hospital mortality in patients with pneumonic chronic obstructive pulmonary disease exacerbations.
    Yu L; Ruan X; Huang W; Huang N; Zeng J; He J; He R; Yang K
    J Asthma; 2024 Mar; 61(3):212-221. PubMed ID: 37738216
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.
    Orchard P; Agakova A; Pinnock H; Burton CD; Sarran C; Agakov F; McKinstry B
    J Med Internet Res; 2018 Sep; 20(9):e263. PubMed ID: 30249589
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED.
    Goto T; Camargo CA; Faridi MK; Yun BJ; Hasegawa K
    Am J Emerg Med; 2018 Sep; 36(9):1650-1654. PubMed ID: 29970272
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease.
    Wang C; Chen X; Du L; Zhan Q; Yang T; Fang Z
    Comput Methods Programs Biomed; 2020 May; 188():105267. PubMed ID: 31841787
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Comparison of the predictive performance of Logistic regression, BP neural network and support vector machine model for the risk of acute exacerbation of readmission in elderly patients with chronic obstructive pulmonary disease within 30 days].
    Zhang R; Chang Y; Zhang X; Lu L; Ding L; Lu H
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2022 Aug; 34(8):819-824. PubMed ID: 36177924
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.