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Why Most Clinical Research Is Not Useful
Why Most Clinical Research Is Not Useful
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Why Most Clinical Research Is Not Useful

Ioannidis, John P A

PLoS medicine, 2016-06, Vol.13 (6), p.e1002049-e1002049 [Periódico revisado por pares]

United States: Public Library of Science

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2
Rescuing US biomedical research from its systemic flaws
Rescuing US biomedical research from its systemic flaws
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Rescuing US biomedical research from its systemic flaws

Albertsa, Bruce ; Kirschner, Marc W. ; Tilghman, Shirley ; Varmusd, Harold

Proceedings of the National Academy of Sciences - PNAS, 2014-04, Vol.111 (16), p.5773-5777 [Periódico revisado por pares]

United States: National Academy of Sciences

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3
Diversity in Clinical and Biomedical Research: A Promise Yet to Be Fulfilled
Diversity in Clinical and Biomedical Research: A Promise Yet to Be Fulfilled
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Diversity in Clinical and Biomedical Research: A Promise Yet to Be Fulfilled

Oh, Sam S ; Galanter, Joshua ; Thakur, Neeta ; Pino-Yanes, Maria ; Barcelo, Nicolas E ; White, Marquitta J ; de Bruin, Danielle M ; Greenblatt, Ruth M ; Bibbins-Domingo, Kirsten ; Wu, Alan H B ; Borrell, Luisa N ; Gunter, Chris ; Powe, Neil R ; Burchard, Esteban G

PLoS medicine, 2015-12, Vol.12 (12), p.e1001918-e1001918 [Periódico revisado por pares]

United States: Public Library of Science

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4
The rise of multiple imputation: a review of the reporting and implementation of the method in medical research
The rise of multiple imputation: a review of the reporting and implementation of the method in medical research
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The rise of multiple imputation: a review of the reporting and implementation of the method in medical research

Hayati Rezvan, Panteha ; Lee, Katherine J ; Simpson, Julie A

BMC medical research methodology, 2015-04, Vol.15 (1), p.30-30, Article 30 [Periódico revisado por pares]

England: BioMed Central Ltd

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5
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
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Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Luo, Wei ; Phung, Dinh ; Tran, Truyen ; Gupta, Sunil ; Rana, Santu ; Karmakar, Chandan ; Shilton, Alistair ; Yearwood, John ; Dimitrova, Nevenka ; Ho, Tu Bao ; Venkatesh, Svetha ; Berk, Michael

Journal of medical Internet research, 2016-12, Vol.18 (12), p.e323-e323 [Periódico revisado por pares]

Canada: Gunther Eysenbach MD MPH, Associate Professor

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6
Knowledge translation in health: how implementation science could contribute more
Knowledge translation in health: how implementation science could contribute more
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Knowledge translation in health: how implementation science could contribute more

Wensing, Michel ; Grol, Richard

BMC medicine, 2019-05, Vol.17 (1), p.88-88, Article 88 [Periódico revisado por pares]

England: BioMed Central Ltd

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7
Correction: Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda
Correction: Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda
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Correction: Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda

Testoni, Federico E ; Carrillo, Mercedes García ; Gagnon, Marc-André ; Rikap, Cecilia ; Blaustein, Matías

PloS one, 2021-11, Vol.16 (11), p.e0260330-e0260330 [Periódico revisado por pares]

San Francisco: Public Library of Science

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8
Risk of Bias in Reports of In Vivo Research: A Focus for Improvement
Risk of Bias in Reports of In Vivo Research: A Focus for Improvement
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Risk of Bias in Reports of In Vivo Research: A Focus for Improvement

Macleod, Malcolm R ; Lawson McLean, Aaron ; Kyriakopoulou, Aikaterini ; Serghiou, Stylianos ; de Wilde, Arno ; Sherratt, Nicki ; Hirst, Theo ; Hemblade, Rachel ; Bahor, Zsanett ; Nunes-Fonseca, Cristina ; Potluru, Aparna ; Thomson, Andrew ; Baginskaite, Julija ; Baginskitae, Julija ; Egan, Kieren ; Vesterinen, Hanna ; Currie, Gillian L ; Churilov, Leonid ; Howells, David W ; Sena, Emily S

PLoS biology, 2015-10, Vol.13 (10), p.e1002273-e1002273 [Periódico revisado por pares]

United States: Public Library of Science

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9
Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge
Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge
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Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge

Jull, Janet ; Giles, Audrey ; Graham, Ian D

Implementation science : IS, 2017-12, Vol.12 (1), p.150-150, Article 150 [Periódico revisado por pares]

England: BioMed Central Ltd

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10
Consolidated Health Economic Evaluation Reporting Standards (CHEERS)—Explanation and Elaboration: A Report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force
Consolidated Health Economic Evaluation Reporting Standards (CHEERS)—Explanation and Elaboration: A Report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force
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Consolidated Health Economic Evaluation Reporting Standards (CHEERS)—Explanation and Elaboration: A Report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force

Husereau, Don, BScPharm, MSc ; Drummond, Michael, PhD ; Petrou, Stavros, MPhil, PhD ; Carswell, Chris, MSc, MRPharmS ; Moher, David, PhD ; Greenberg, Dan, PhD ; Augustovski, Federico, MD, MSc, PhD ; Briggs, Andrew H., MSc (York), MSc (Oxon), DPhil (Oxon) ; Mauskopf, Josephine, PhD ; Loder, Elizabeth, MD, MPH

Value in health, 2013-03, Vol.16 (2), p.231-250 [Periódico revisado por pares]

New York, NY: Elsevier Inc

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