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 *

123 related articles for article (PubMed ID: 37729604)

  • 1. Comparison between linear regression and four different machine learning methods in selecting risk factors for osteoporosis in a Chinese female aged cohort.
    Tzou SJ; Peng CH; Huang LY; Chen FY; Kuo CH; Wu CZ; Chu TW
    J Chin Med Assoc; 2023 Nov; 86(11):1028-1036. PubMed ID: 37729604
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparison of multiple linear regression and machine learning methods in predicting cognitive function in older Chinese type 2 diabetes patients.
    Liu CH; Peng CH; Huang LY; Chen FY; Kuo CH; Wu CZ; Cheng YF
    BMC Neurol; 2024 Jan; 24(1):11. PubMed ID: 38166825
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without non-alcoholic fatty liver.
    Chen IC; Chou LJ; Huang SC; Chu TW; Lee SS
    World J Clin Cases; 2024 May; 12(15):2506-2521. PubMed ID: 38817230
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine Learning Can Improve Clinical Detection of Low BMD: The DXA-HIP Study.
    E E; Wang T; Yang L; Dempsey M; Brennan A; Yu M; Chan WP; Whelan B; Silke C; O'Sullivan M; Rooney B; McPartland A; O'Malley G; Carey JJ
    J Clin Densitom; 2021; 24(4):527-537. PubMed ID: 33187864
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
    Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
    BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Disability risk prediction model based on machine learning among Chinese healthy older adults: results from the China Health and Retirement Longitudinal Study.
    Han Y; Wang S
    Front Public Health; 2023; 11():1271595. PubMed ID: 38026309
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.
    Wang J; Chen H; Wang H; Liu W; Peng D; Zhao Q; Xiao M
    J Med Internet Res; 2023 Apr; 25():e43815. PubMed ID: 37023416
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine Learning Predictive Models for Evaluating Risk Factors Affecting Sperm Count: Predictions Based on Health Screening Indicators.
    Huang HH; Hsieh SJ; Chen MS; Jhou MJ; Liu TC; Shen HL; Yang CT; Hung CC; Yu YY; Lu CJ
    J Clin Med; 2023 Feb; 12(3):. PubMed ID: 36769868
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
    Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
    Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison between Machine Learning and Multiple Linear Regression to Identify Abnormal Thallium Myocardial Perfusion Scan in Chinese Type 2 Diabetes.
    Lin JD; Pei D; Chen FY; Wu CZ; Lu CH; Huang LY; Kuo CH; Kuo SW; Chen YL
    Diagnostics (Basel); 2022 Jul; 12(7):. PubMed ID: 35885524
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
    Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Prediction Model for Osteoporosis Risk Using a Machine-Learning Approach and Its Validation in a Large Cohort.
    Wu X; Park S
    J Korean Med Sci; 2023 May; 38(21):e162. PubMed ID: 37270917
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Using Machine Learning to Identify the Relationships between Demographic, Biochemical, and Lifestyle Parameters and Plasma Vitamin D Concentration in Healthy Premenopausal Chinese Women.
    Wang CK; Chang CY; Chu TW; Liang YJ
    Life (Basel); 2023 Nov; 13(12):. PubMed ID: 38137858
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?
    El-Galaly A; Grazal C; Kappel A; Nielsen PT; Jensen SL; Forsberg JA
    Clin Orthop Relat Res; 2020 Sep; 478(9):2088-2101. PubMed ID: 32667760
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Machine Learning-Based Preclinical Osteoporosis Screening Tool (POST): Model Development and Validation Study.
    Yang Q; Cheng H; Qin J; Loke AY; Ngai FW; Chong KC; Zhang D; Gao Y; Wang HH; Liu Z; Hao C; Xie YJ
    JMIR Aging; 2023 Nov; 6():e46791. PubMed ID: 37986117
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of metabolic and pre-metabolic syndromes using machine learning models with anthropometric, lifestyle, and biochemical factors from a middle-aged population in Korea.
    Kim J; Mun S; Lee S; Jeong K; Baek Y
    BMC Public Health; 2022 Apr; 22(1):664. PubMed ID: 35387629
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application of machine learning approaches for osteoporosis risk prediction in postmenopausal women.
    Shim JG; Kim DW; Ryu KH; Cho EA; Ahn JH; Kim JI; Lee SH
    Arch Osteoporos; 2020 Oct; 15(1):169. PubMed ID: 33097976
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density.
    Ekundayo TC; Ijabadeniyi OA; Igbinosa EO; Okoh AI
    Environ Pollut; 2023 Jan; 317():120734. PubMed ID: 36455774
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting crop root concentration factors of organic contaminants with machine learning models.
    Gao F; Shen Y; Brett Sallach J; Li H; Zhang W; Li Y; Liu C
    J Hazard Mater; 2022 Feb; 424(Pt B):127437. PubMed ID: 34678561
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning approaches for the prediction of bone mineral density by using genomic and phenotypic data of 5130 older men.
    Wu Q; Nasoz F; Jung J; Bhattarai B; Han MV; Greenes RA; Saag KG
    Sci Rep; 2021 Feb; 11(1):4482. PubMed ID: 33627720
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.