BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

120 related articles for article (PubMed ID: 38564961)

  • 1. Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.
    Kim K; Yoon Y; Shin S
    Int J Med Inform; 2024 Jun; 186():105441. PubMed ID: 38564961
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of Problematic Smartphone Use: A Machine Learning Approach.
    Lee J; Kim W
    Int J Environ Res Public Health; 2021 Jun; 18(12):. PubMed ID: 34203674
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.
    Shin S; Kim K
    Asian J Psychiatr; 2023 Oct; 88():103725. PubMed ID: 37595385
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Association of Smartphone Use With Body Image Distortion and Weight Loss Behaviors in Korean Adolescents.
    Kwon S; Kim R; Lee JT; Kim J; Song S; Kim S; Oh H
    JAMA Netw Open; 2022 May; 5(5):e2213237. PubMed ID: 35594044
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Smartphone use patterns and problematic smartphone use among preschool children.
    Park JH; Park M
    PLoS One; 2021; 16(3):e0244276. PubMed ID: 33647038
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Association between smartphone overdependence and generalized anxiety disorder among Korean adolescents.
    Lee YS; Joo JH; Shin J; Nam CM; Park EC
    J Affect Disord; 2023 Jan; 321():108-113. PubMed ID: 36283537
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Gender Differences in Parental Impact on Problematic Smartphone Use among Korean Adolescents.
    Son H; Park S; Han G
    Int J Environ Res Public Health; 2021 Jan; 18(2):. PubMed ID: 33429898
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Smartphone use and addiction during the coronavirus disease 2019 (COVID-19) pandemic: cohort study on 184 Italian children and adolescents.
    Serra G; Lo Scalzo L; Giuffrè M; Ferrara P; Corsello G
    Ital J Pediatr; 2021 Jul; 47(1):150. PubMed ID: 34215311
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study.
    Bae SW; Suffoletto B; Zhang T; Chung T; Ozolcer M; Islam MR; Dey AK
    JMIR Form Res; 2023 May; 7():e39862. PubMed ID: 36809294
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Latent classes of smartphone dependency trajectories and predictors of classes among middle school students in South Korea.
    Kim E; Jo J; Song MK
    J Pediatr Nurs; 2023; 73():44-52. PubMed ID: 37639987
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Impact of COVID-19 on Adolescents' Smartphone Addiction in South Korea.
    Chun J; Lee HK; Jeon H; Kim J; Lee S
    Soc Work Public Health; 2023 May; 38(4):268-280. PubMed ID: 36227775
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.
    Zakariaee SS; Naderi N; Ebrahimi M; Kazemi-Arpanahi H
    Sci Rep; 2023 Jul; 13(1):11343. PubMed ID: 37443373
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.
    Jung JS; Park SJ; Kim EY; Na KS; Kim YJ; Kim KG
    PLoS One; 2019; 14(6):e0217639. PubMed ID: 31170212
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Smartphone usage and overdependence risk among middle-aged and older adults: a cross-sectional study.
    Kim SH; Kim YH; Lee CH; Lee Y
    BMC Public Health; 2024 Feb; 24(1):413. PubMed ID: 38331734
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.
    Chung H; Ko H; Kang WS; Kim KW; Lee H; Park C; Song HO; Choi TY; Seo JH; Lee J
    J Med Internet Res; 2021 Apr; 23(4):e27060. PubMed ID: 33764883
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Association between Smartphone Addiction and Suicide.
    Shinetsetseg O; Jung YH; Park YS; Park EC; Jang SY
    Int J Environ Res Public Health; 2022 Sep; 19(18):. PubMed ID: 36141872
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.
    Lee S; Kang WS; Kim DW; Seo SH; Kim J; Jeong ST; Yon DK; Lee J
    J Med Internet Res; 2023 Aug; 25():e49283. PubMed ID: 37642984
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Smartphones dependency risk analysis using machine-learning predictive models.
    Giraldo-Jiménez CF; Gaviria-Chavarro J; Sarria-Paja M; Bermeo Varón LA; Villarejo-Mayor JJ; Rodacki ALF
    Sci Rep; 2022 Dec; 12(1):22649. PubMed ID: 36587033
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The Effects of Korean Parents' Smartphone Addiction on Korean Children's Smartphone Addiction: Moderating Effects of Children's Gender and Age.
    Son HG; Cho HJ; Jeong KH
    Int J Environ Res Public Health; 2021 Jun; 18(13):. PubMed ID: 34206185
    [No Abstract]   [Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 6.