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 *

67 related articles for article (PubMed ID: 33896755)

  • 1. Development and validation of the type 2 diabetes mellitus 10-year risk score prediction models from survey data.
    Stiglic G; Wang F; Sheikh A; Cilar L
    Prim Care Diabetes; 2021 Aug; 15(4):699-705. PubMed ID: 33896755
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol.
    Salinero-Fort MÁ; de Burgos-Lunar C; Mostaza Prieto J; Lahoz Rallo C; Abánades-Herranz JC; Gómez-Campelo P; Laguna Cuesta F; Estirado De Cabo E; García Iglesias F; González Alegre T; Fernández Puntero B; Montesano Sánchez L; Vicent López D; Cornejo Del Río V; Fernández García PJ; Sabín Rodríguez C; López López S; Patrón Barandío P;
    BMJ Open; 2015 Jul; 5(7):e007195. PubMed ID: 26220868
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of type 2 diabetes mellitus based on nutrition data.
    Katsimpris A; Brahim A; Rathmann W; Peters A; Strauch K; Flaquer A
    J Nutr Sci; 2021; 10():e46. PubMed ID: 34221364
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Evaluation of the Finnish Diabetes Risk Score as a screening tool for undiagnosed type 2 diabetes and dysglycaemia among early middle-aged adults in a large-scale European cohort. The Feel4Diabetes-study.
    Mavrogianni C; Lambrinou CP; Androutsos O; Lindström J; Kivelä J; Cardon G; Huys N; Tsochev K; Iotova V; Chakarova N; Rurik I; Moreno LA; Liatis S; Makrilakis K; Manios Y;
    Diabetes Res Clin Pract; 2019 Apr; 150():99-110. PubMed ID: 30796939
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population.
    Štiglic G; Kocbek P; Cilar L; Fijačko N; Stožer A; Zaletel J; Sheikh A; Povalej Bržan P
    Diabet Med; 2018 May; 35(5):640-649. PubMed ID: 29460977
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predictors of undiagnosed prevalent type 2 diabetes - The Danish General Suburban Population Study.
    Heltberg A; Andersen JS; Sandholdt H; Siersma V; Kragstrup J; Ellervik C
    Prim Care Diabetes; 2018 Feb; 12(1):13-22. PubMed ID: 28964672
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A simple nomogram score for screening patients with type 2 diabetes to detect those with hypertension: A cross-sectional study based on a large community survey in China.
    Xue M; Liu L; Wang S; Su Y; Lv K; Zhang M; Yao H
    PLoS One; 2020; 15(8):e0236957. PubMed ID: 32764769
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.
    Choi BG; Rha SW; Kim SW; Kang JH; Park JY; Noh YK
    Yonsei Med J; 2019 Feb; 60(2):191-199. PubMed ID: 30666841
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A risk-score model for predicting risk of type 2 diabetes mellitus in a rural Chinese adult population: A cohort study with a 6-year follow-up.
    Zhang H; Wang C; Ren Y; Wang B; Yang X; Zhao Y; Han C; Zhou J; Zhang L; Qi M; Zhai Y; Pang C; Yin L; Zhao J; Hu D; Zhang M
    Diabetes Metab Res Rev; 2017 Oct; 33(7):. PubMed ID: 28608942
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans.
    Lee JW; Lim NK; Park HY
    BMC Endocr Disord; 2018 May; 18(1):33. PubMed ID: 29843706
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study.
    Wilson PW; Meigs JB; Sullivan L; Fox CS; Nathan DM; D'Agostino RB
    Arch Intern Med; 2007 May; 167(10):1068-74. PubMed ID: 17533210
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning Models in Type 2 Diabetes Risk Prediction: Results from a Cross-sectional Retrospective Study in Chinese Adults.
    Xiong XL; Zhang RX; Bi Y; Zhou WH; Yu Y; Zhu DL
    Curr Med Sci; 2019 Aug; 39(4):582-588. PubMed ID: 31346994
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Establishment of Clinical Prediction Model Based on the Study of Risk Factors of Stroke in Patients With Type 2 Diabetes Mellitus.
    Shi R; Zhang T; Sun H; Hu F
    Front Endocrinol (Lausanne); 2020; 11():559. PubMed ID: 32982965
    [No Abstract]   [Full Text] [Related]  

  • 14. External validation of a risk assessment model to adjust the frequency of eye-screening visits in patients with diabetes mellitus.
    Soto-Pedre E; Pinies JA; Hernaez-Ortega MC
    J Diabetes Complications; 2015; 29(4):508-11. PubMed ID: 25725582
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Derivation and validation of diabetes risk score for urban Asian Indians.
    Ramachandran A; Snehalatha C; Vijay V; Wareham NJ; Colagiuri S
    Diabetes Res Clin Pract; 2005 Oct; 70(1):63-70. PubMed ID: 16126124
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Pregnancy-associated plasma protein-A is a stronger predictor for adverse cardiovascular outcomes after acute coronary syndrome in type-2 diabetes mellitus.
    Li WP; Neradilek MB; Gu FS; Isquith DA; Sun ZJ; Wu X; Li HW; Zhao XQ
    Cardiovasc Diabetol; 2017 Apr; 16(1):45. PubMed ID: 28381225
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Clinical risk scoring for predicting non-alcoholic fatty liver disease in metabolic syndrome patients (NAFLD-MS score).
    Saokaew S; Kanchanasuwan S; Apisarnthanarak P; Charoensak A; Charatcharoenwitthaya P; Phisalprapa P; Chaiyakunapruk N
    Liver Int; 2017 Oct; 37(10):1535-1543. PubMed ID: 28294515
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques.
    Li J; Chen Q; Hu X; Yuan P; Cui L; Tu L; Cui J; Huang J; Jiang T; Ma X; Yao X; Zhou C; Lu H; Xu J
    Int J Med Inform; 2021 May; 149():104429. PubMed ID: 33647600
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Development and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries.
    Suemoto CK; Ueda P; Beltrán-Sánchez H; Lebrão ML; Duarte YA; Wong R; Danaei G
    J Gerontol A Biol Sci Med Sci; 2017 Mar; 72(3):410-416. PubMed ID: 27522061
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Receiver Operating Characteristic Curve-Based Prediction Model for Periodontal Disease Updated With the Calibrated Community Periodontal Index.
    Su CW; Yen AM; Lai H; Chen HH; Chen SL
    J Periodontol; 2017 Dec; 88(12):1348-1355. PubMed ID: 28753099
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 4.