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 *

107 related articles for article (PubMed ID: 34496418)

  • 1. A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data.
    Sun Y; Butler A; Diallo I; Kim JH; Ta C; Rogers JR; Liu H; Weng C
    Appl Clin Inform; 2021 Aug; 12(4):816-825. PubMed ID: 34496418
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multivariate analysis of the population representativeness of related clinical studies.
    He Z; Ryan P; Hoxha J; Wang S; Carini S; Sim I; Weng C
    J Biomed Inform; 2016 Apr; 60():66-76. PubMed ID: 26820188
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials.
    Kim JH; Ta CN; Liu C; Sung C; Butler AM; Stewart LA; Ena L; Rogers JR; Lee J; Ostropolets A; Ryan PB; Liu H; Lee SM; Elkind MSV; Weng C
    J Am Med Inform Assoc; 2021 Jan; 28(1):14-22. PubMed ID: 33260201
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparing and Contrasting A Priori and A Posteriori Generalizability Assessment of Clinical Trials on Type 2 Diabetes Mellitus.
    He Z; Gonzalez-Izquierdo A; Denaxas S; Sura A; Guo Y; Hogan WR; Shenkman E; Bian J
    AMIA Annu Symp Proc; 2017; 2017():849-858. PubMed ID: 29854151
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0.
    Sen A; Goldstein A; Chakrabarti S; Shang N; Kang T; Yaman A; Ryan PB; Weng C
    J Am Med Inform Assoc; 2018 Mar; 25(3):239-247. PubMed ID: 29025047
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Claims-based studies of oral glucose-lowering medications can achieve balance in critical clinical variables only observed in electronic health records.
    Patorno E; Gopalakrishnan C; Franklin JM; Brodovicz KG; Masso-Gonzalez E; Bartels DB; Liu J; Schneeweiss S
    Diabetes Obes Metab; 2018 Apr; 20(4):974-984. PubMed ID: 29206336
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A knowledge base of clinical trial eligibility criteria.
    Liu H; Chi Y; Butler A; Sun Y; Weng C
    J Biomed Inform; 2021 May; 117():103771. PubMed ID: 33813032
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials.
    Sen A; Ryan PB; Goldstein A; Chakrabarti S; Wang S; Koski E; Weng C
    Ann N Y Acad Sci; 2017 Jan; 1387(1):34-43. PubMed ID: 27598694
    [TBL] [Abstract][Full Text] [Related]  

  • 9. PROTECT Trial: A cluster-randomized study with hydroxychloroquine versus observational support for prevention or early-phase treatment of Coronavirus disease (COVID-19): A structured summary of a study protocol for a randomized controlled trial.
    Nanni O; Viale P; Vertogen B; Lilli C; Zingaretti C; Donati C; Masini C; Monti M; Serra P; Vespignani R; Grossi V; Biggeri A; Scarpi E; Galardi F; Bertoni L; Colamartini A; Falcini F; Altini M; Massa I; Gaggeri R; Martinelli G
    Trials; 2020 Jul; 21(1):689. PubMed ID: 32736597
    [TBL] [Abstract][Full Text] [Related]  

  • 10. GIST 2.0: A scalable multi-trait metric for quantifying population representativeness of individual clinical studies.
    Sen A; Chakrabarti S; Goldstein A; Wang S; Ryan PB; Weng C
    J Biomed Inform; 2016 Oct; 63():325-336. PubMed ID: 27600407
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning enabled subgroup analysis with real-world data to inform clinical trial eligibility criteria design.
    Xu J; Zhang H; Zhang H; Bian J; Wang F
    Sci Rep; 2023 Jan; 13(1):613. PubMed ID: 36635438
    [TBL] [Abstract][Full Text] [Related]  

  • 12. How representative of a general type 2 diabetes population are patients included in cardiovascular outcome trials with SGLT2 inhibitors? A large European observational study.
    Birkeland KI; Bodegard J; Norhammar A; Kuiper JG; Georgiado E; Beekman-Hendriks WL; Thuresson M; Pignot M; Herings RMC; Kooy A
    Diabetes Obes Metab; 2019 Apr; 21(4):968-974. PubMed ID: 30537226
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessing the Collective Population Representativeness of Related Type 2 Diabetes Trials by Combining Public Data from ClinicalTrials.gov and NHANES.
    He Z; Wang S; Borhanian E; Weng C
    Stud Health Technol Inform; 2015; 216():569-73. PubMed ID: 26262115
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials.
    Miotto R; Weng C
    J Am Med Inform Assoc; 2015 Apr; 22(e1):e141-50. PubMed ID: 25769682
    [TBL] [Abstract][Full Text] [Related]  

  • 15. SPIKE-1: A Randomised Phase II/III trial in a community setting, assessing use of camostat in reducing the clinical progression of COVID-19 by blocking SARS-CoV-2 Spike protein-initiated membrane fusion.
    Halford S; Wan S; Dragoni I; Silvester J; Nazarov B; Anthony D; Anthony S; Ladds E; Norrie J; Dhaliwal K;
    Trials; 2021 Aug; 22(1):550. PubMed ID: 34412682
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The opportunities and challenges of pragmatic point-of-care randomised trials using routinely collected electronic records: evaluations of two exemplar trials.
    van Staa TP; Dyson L; McCann G; Padmanabhan S; Belatri R; Goldacre B; Cassell J; Pirmohamed M; Torgerson D; Ronaldson S; Adamson J; Taweel A; Delaney B; Mahmood S; Baracaia S; Round T; Fox R; Hunter T; Gulliford M; Smeeth L
    Health Technol Assess; 2014 Jul; 18(43):1-146. PubMed ID: 25011568
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Conformity between protocol eligibility criteria for electronic patient identification: a comparison of clinical trials.
    Kamauu A; Agbor S; Kamauu A
    Stud Health Technol Inform; 2013; 192():1167. PubMed ID: 23920941
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Leveraging electronic health record data for clinical trial planning by assessing eligibility criteria's impact on patient count and safety.
    Rogers JR; Pavisic J; Ta CN; Liu C; Soroush A; Kuen Cheung Y; Hripcsak G; Weng C
    J Biomed Inform; 2022 Mar; 127():104032. PubMed ID: 35189334
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluation of the representativeness and generalizability of Japanese clinical trials for localized rectal/colon cancer: Comparing participants in the Japan Clinical Oncology Group study with patients in Japanese registries.
    Miyamoto K; Wakabayashi M; Mizusawa J; Nakamura K; Katayama H; Higashi T; Inomata M; Kitano S; Fujita S; Kanemitsu Y; Fukuda H
    Eur J Surg Oncol; 2020 Sep; 46(9):1642-1648. PubMed ID: 32340817
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence.
    Köpcke F; Trinczek B; Majeed RW; Schreiweis B; Wenk J; Leusch T; Ganslandt T; Ohmann C; Bergh B; Röhrig R; Dugas M; Prokosch HU
    BMC Med Inform Decis Mak; 2013 Mar; 13():37. PubMed ID: 23514203
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.