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 *

120 related articles for article (PubMed ID: 38959248)

  • 1. Predicting sexually transmitted infections among men who have sex with men in Zimbabwe using deep learning and ensemble machine learning models.
    Mugurungi O; Mbunge E; Birri-Makota R; Chingombe I; Mapingure M; Moyo B; Mpofu A; Batani J; Muchemwa B; Samba C; Murigo D; Sibindi M; Moyo E; Dzinamarira T; Musuka G
    PLOS Digit Health; 2024 Jul; 3(7):e0000541. PubMed ID: 38959248
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting HIV Status among Men Who Have Sex with Men in Bulawayo & Harare, Zimbabwe Using Bio-Behavioural Data, Recurrent Neural Networks, and Machine Learning Techniques.
    Chingombe I; Dzinamarira T; Cuadros D; Mapingure MP; Mbunge E; Chaputsira S; Madziva R; Chiurunge P; Samba C; Herrera H; Murewanhema G; Mugurungi O; Musuka G
    Trop Med Infect Dis; 2022 Sep; 7(9):. PubMed ID: 36136641
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.
    He J; Li J; Jiang S; Cheng W; Jiang J; Xu Y; Yang J; Zhou X; Chai C; Wu C
    Front Public Health; 2022; 10():967681. PubMed ID: 36091522
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Using machine learning approaches to predict timely clinic attendance and the uptake of HIV/STI testing post clinic reminder messages.
    Xu X; Fairley CK; Chow EPF; Lee D; Aung ET; Zhang L; Ong JJ
    Sci Rep; 2022 May; 12(1):8757. PubMed ID: 35610227
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study.
    Xu X; Yu Z; Ge Z; Chow EPF; Bao Y; Ong JJ; Li W; Wu J; Fairley CK; Zhang L
    J Med Internet Res; 2022 Aug; 24(8):e37850. PubMed ID: 36006685
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Clinical features-based machine learning models to separate sexually transmitted infections from other skin diagnoses.
    Soe NN; Latt PM; Yu Z; Lee D; Kim CM; Tran D; Ong JJ; Ge Z; Fairley CK; Zhang L
    J Infect; 2024 Apr; 88(4):106128. PubMed ID: 38452934
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Self-reported history of sexually transmissible infections (STIs) and STI-related utilization of the German health care system by men who have sex with men: data from a large convenience sample.
    Schmidt AJ; Marcus U
    BMC Infect Dis; 2011 May; 11():132. PubMed ID: 21592342
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Use of geosocial networking applications is independently associated with diagnosis of STI among men who have sex with men testing for STIs: findings from the cross-sectional MSM Internet Survey Ireland (MISI) 2015.
    O'Connor L; O'Donnell K; Barrett P; Hickson FCI; McCartney D; Quinlan M; Barrasa A; Fitzgerald M; Igoe D
    Sex Transm Infect; 2019 Jun; 95(4):279-284. PubMed ID: 30518621
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An Ensemble Machine Learning and Data Mining Approach to Enhance Stroke Prediction.
    Wijaya R; Saeed F; Samimi P; Albarrak AM; Qasem SN
    Bioengineering (Basel); 2024 Jul; 11(7):. PubMed ID: 39061754
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The epidemiology of HIV and other sexually transmitted infections in African, Caribbean and Black men in Toronto, Canada.
    Nelson LE; Tharao W; Husbands W; Sa T; Zhang N; Kushwaha S; Absalom D; Kaul R
    BMC Infect Dis; 2019 Mar; 19(1):294. PubMed ID: 30925906
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Regular STI testing amongst men who have sex with men and use social media is suboptimal - a cross-sectional study.
    Frankis J; Goodall L; Clutterbuck D; Abubakari AR; Flowers P
    Int J STD AIDS; 2017 May; 28(6):573-583. PubMed ID: 26945592
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Risk factors for HIV and STI diagnosis in a community-based HIV/STI testing and counselling site for men having sex with men (MSM) in a large German city in 2011-2012.
    Marcus U; Ort J; Grenz M; Eckstein K; Wirtz K; Wille A
    BMC Infect Dis; 2015 Jan; 15():14. PubMed ID: 25582975
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting the diagnosis of HIV and sexually transmitted infections among men who have sex with men using machine learning approaches.
    Bao Y; Medland NA; Fairley CK; Wu J; Shang X; Chow EPF; Xu X; Ge Z; Zhuang X; Zhang L
    J Infect; 2021 Jan; 82(1):48-59. PubMed ID: 33189772
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Sexually transmitted infection diagnoses among Hispanic immigrant and migrant men who have sex with men in the United States.
    Valverde EE; DiNenno EA; Schulden JD; Oster A; Painter T
    Int J STD AIDS; 2016 Nov; 27(13):1162-1169. PubMed ID: 26464501
    [TBL] [Abstract][Full Text] [Related]  

  • 15. High HIV seroprevalence, rectal STIs and risky sexual behaviour in men who have sex with men in Dar es Salaam and Tanga, Tanzania.
    Ross MW; Nyoni J; Ahaneku HO; Mbwambo J; McClelland RS; McCurdy SA
    BMJ Open; 2014 Aug; 4(8):e006175. PubMed ID: 25168042
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Sexually transmitted infections in Western Europe among HIV-positive men who have sex with men.
    Dougan S; Evans BG; Elford J
    Sex Transm Dis; 2007 Oct; 34(10):783-90. PubMed ID: 17495592
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China.
    Li X; Zhang H; Zhao S; Tang K
    JMIR Public Health Surveill; 2023 Jan; 9():e41162. PubMed ID: 36696166
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data.
    Hu M; Peng H; Zhang X; Wang L; Ren J
    BMC Med Inform Decis Mak; 2024 Jan; 24(1):24. PubMed ID: 38267946
    [TBL] [Abstract][Full Text] [Related]  

  • 19. High burden of self-reported sexually transmitted infections among key populations in Mozambique: the urgent need for an integrated surveillance system.
    Boothe MAS; Comé C; Semá Baltazar C; Chicuecue N; Seleme J; Chitsondzo Langa D; Sathane I; Raymond HF; Fazito E; Temmerman M; Luchters S
    BMC Infect Dis; 2020 Aug; 20(1):636. PubMed ID: 32854638
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 6.