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 *

202 related articles for article (PubMed ID: 34509878)

  • 21. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence.
    Collins GS; Dhiman P; Andaur Navarro CL; Ma J; Hooft L; Reitsma JB; Logullo P; Beam AL; Peng L; Van Calster B; van Smeden M; Riley RD; Moons KG
    BMJ Open; 2021 Jul; 11(7):e048008. PubMed ID: 34244270
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.
    Collins GS; Reitsma JB; Altman DG; Moons KG
    Diabet Med; 2015 Feb; 32(2):146-54. PubMed ID: 25600898
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.
    Collins GS; Reitsma JB; Altman DG; Moons KG
    J Clin Epidemiol; 2015 Feb; 68(2):134-43. PubMed ID: 25579640
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review.
    Abdulaziz KE; Perry JJ; Yadav K; Dowlatshahi D; Stiell IG; Wells GA; Taljaard M
    Diagn Progn Res; 2022 May; 6(1):9. PubMed ID: 35585563
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Reporting and risk of bias of prediction models based on machine learning methods in preterm birth: A systematic review.
    Yang Q; Fan X; Cao X; Hao W; Lu J; Wei J; Tian J; Yin M; Ge L
    Acta Obstet Gynecol Scand; 2023 Jan; 102(1):7-14. PubMed ID: 36397723
    [TBL] [Abstract][Full Text] [Related]  

  • 26. TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models.
    Zamanipoor Najafabadi AH; Ramspek CL; Dekker FW; Heus P; Hooft L; Moons KGM; Peul WC; Collins GS; Steyerberg EW; van Diepen M
    BMJ Open; 2020 Sep; 10(9):e041537. PubMed ID: 32948578
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Prediction models for skin tears in the elderly: A systematic review and meta-analysis.
    Fan S; Jiang H; Shen J; Lin H; Yang L; Yu D; Zhang M; Zheng N; Chen L
    Geriatr Nurs; 2024; 59():103-112. PubMed ID: 38996767
    [TBL] [Abstract][Full Text] [Related]  

  • 28. New Guideline for the Reporting of Studies Developing, Validating, or Updating a Multivariable Clinical Prediction Model: The TRIPOD Statement.
    Moons KG; Altman DG; Reitsma JB; Collins GS;
    Adv Anat Pathol; 2015 Sep; 22(5):303-5. PubMed ID: 26262512
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Examining Bias and Reporting in Oral Health Prediction Modeling Studies.
    Du M; Haag D; Song Y; Lynch J; Mittinty M
    J Dent Res; 2020 Apr; 99(4):374-387. PubMed ID: 32028825
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Risk Prediction Models for Cardiotoxicity of Chemotherapy Among Patients With Breast Cancer: A Systematic Review.
    Kaboré EG; Macdonald C; Kaboré A; Didier R; Arveux P; Meda N; Boutron-Ruault MC; Guenancia C
    JAMA Netw Open; 2023 Feb; 6(2):e230569. PubMed ID: 36821108
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review.
    Dhiman P; Ma J; Andaur Navarro CL; Speich B; Bullock G; Damen JAA; Hooft L; Kirtley S; Riley RD; Van Calster B; Moons KGM; Collins GS
    BMC Med Res Methodol; 2022 Apr; 22(1):101. PubMed ID: 35395724
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Bias and Reporting Quality of Clinical Prognostic Models for Idiopathic Pulmonary Fibrosis: A Cross-Sectional Study.
    Di J; Li X; Yang J; Li L; Yu X
    Risk Manag Healthc Policy; 2022; 15():1189-1201. PubMed ID: 35702399
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Improvements Are Needed in the Adherence to the TRIPOD Statement for Clinical Prediction Models for Patients With Spinal Pain or Osteoarthritis: A Metaresearch Study.
    Feller D; Wingbermuhle R; Berg B; Vigdal ØN; Innocenti T; Grotle M; Ostelo R; Chiarotto A
    J Pain; 2024 Nov; 25(11):104624. PubMed ID: 39002741
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.
    Dhiman P; Ma J; Navarro CA; Speich B; Bullock G; Damen JA; Kirtley S; Hooft L; Riley RD; Van Calster B; Moons KGM; Collins GS
    J Clin Epidemiol; 2021 Oct; 138():60-72. PubMed ID: 34214626
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Transparent Reporting of Multivariable Prediction Models in Journal and Conference Abstracts: TRIPOD for Abstracts.
    Heus P; Reitsma JB; Collins GS; Damen JAAG; Scholten RJPM; Altman DG; Moons KGM; Hooft L
    Ann Intern Med; 2020 Jun; ():. PubMed ID: 32479165
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine learning prediction models in orthopedic surgery: A systematic review in transparent reporting.
    Groot OQ; Ogink PT; Lans A; Twining PK; Kapoor ND; DiGiovanni W; Bindels BJJ; Bongers MER; Oosterhoff JHF; Karhade AV; Oner FC; Verlaan JJ; Schwab JH
    J Orthop Res; 2022 Feb; 40(2):475-483. PubMed ID: 33734466
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Standardization of risk prediction model reporting in cancer-associated thrombosis: Communication from the ISTH SSC subcommittee on hemostasis and malignancy.
    Sanfilippo KM; Wang TF; Carrier M; Falanga A; Gage BF; Khorana AA; Maraveyas A; Soff GA; Wells PS; Zwicker JI
    J Thromb Haemost; 2022 Aug; 20(8):1920-1927. PubMed ID: 35635332
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Uniformity in measuring adherence to reporting guidelines: the example of TRIPOD for assessing completeness of reporting of prediction model studies.
    Heus P; Damen JAAG; Pajouheshnia R; Scholten RJPM; Reitsma JB; Collins GS; Altman DG; Moons KGM; Hooft L
    BMJ Open; 2019 Apr; 9(4):e025611. PubMed ID: 31023756
    [TBL] [Abstract][Full Text] [Related]  

  • 39. An Appraisal of the Quality of Development and Reporting of Predictive Models in Neurosurgery: A Systematic Review.
    Khalid SI; Massaad E; Roy JM; Thomson K; Mirpuri P; Kiapour A; Shin JH
    Neurosurgery; 2024 Jun; ():. PubMed ID: 38940578
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Protocol for the development and validation of a risk prediction model for stillbirths from 35 weeks gestation in Australia.
    Sexton JK; Coory M; Kumar S; Smith G; Gordon A; Chambers G; Pereira G; Raynes-Greenow C; Hilder L; Middleton P; Bowman A; Lieske SN; Warrilow K; Morris J; Ellwood D; Flenady V
    Diagn Progn Res; 2020 Dec; 4(1):21. PubMed ID: 33323131
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.