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A practice model for interprofessional education in a first year anatomy class

Journal of interprofessional care, 2019-05, Vol.33 (3), p.313-320

2019

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Promoting deeper learning in pharmacy education using team-based learning

African journal of health professions education, 2021-07, Vol.13 (2), p.105

2021

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Lateral force microscope calibration using a modified atomic force microscope cantilever

Review of scientific instruments, 2007-10, Vol.78 (10), p.106102-106102-3

Reitsma, M. G.

2007

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Nationally hosted tax intervention : exploring South African students’ perceptions of its usefulness to develop pervasive skills

South African journal of higher education, 2018-09, Vol.32 (4), p.245-262

2018

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Wear of a single asperity using Lateral Force Microscopy

Tribology letters, 2006-12, Vol.24 (3), p.257-263

2006

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Field trips as an intervention to enhance pharmacy students’ positive perception of a management module in their final year: A pilot study

African journal of health professions education, 2015-11, Vol.7 (2), p.212

2015

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Giant pop-ins in nanoindented silicon and germanium caused by lateral cracking

Journal of materials research, 2008-02, Vol.23 (2), p.297-301

2008

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Rapid Communications: Giant pop-ins in nanoindented silicon and germanium caused by lateral cracking

Journal of materials research, 2008-02, Vol.23 (2), p.297-301

2008

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Quantitative comparison of three calibration techniques for the lateral force microscope

Review of scientific instruments, 2001-08, Vol.72 (8), p.3304-3312

2001

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Observed transition from linear to non-linear friction–load behavior using a lateral force microscope

Applied surface science, 2006-05, Vol.252 (14), p.4964-4968

2006

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Thusa Phase II: The design of a nutrition intervention education programme

Journal of Family Ecology and Consumer Sciences /Tydskrif vir Gesinsekologie en Verbruikerswetenskappe, 2010-03, Vol.27 (2)

2010

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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

BMJ (Online), 2015-01, Vol.350 (jan07 4), p.g7594-g7594

2015

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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

BMC medicine, 2015-01, Vol.13 (1), p.1-1

2015

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Quantifying the Accuracy of a Diagnostic Test or Marker

Clinical chemistry (Baltimore, Md.), 2012-09, Vol.58 (9), p.1292-1301

2012

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Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist

PLoS medicine, 2014-10, Vol.11 (10), p.e1001744-e1001744

2014

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Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement

Annals of internal medicine, 2015-01, Vol.162 (1), p.55-63

2015

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Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement

British journal of surgery, 2015-02, Vol.102 (3), p.148-158

2015

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PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

Annals of internal medicine, 2019-01, Vol.170 (1), p.51

2019

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PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

Annals of internal medicine, 2019-01, Vol.170 (1), p.W1

2019

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Sample size for binary logistic prediction models: Beyond events per variable criteria

Statistical methods in medical research, 2019-08, Vol.28 (8), p.2455-2474

2019

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STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies

Radiology, 2015-12, Vol.277 (3), p.826-832

2015

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Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

Annals of internal medicine, 2015-01, Vol.162 (1), p.W1-W73

2015

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Beyond Diagnostic Accuracy: The Clinical Utility of Diagnostic Tests

Clinical chemistry (Baltimore, Md.), 2012-12, Vol.58 (12), p.1636-1643

2012

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A guide to systematic review and meta-analysis of prediction model performance

BMJ (Online), 2017-01, Vol.356, p.i6460

2017

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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

BMJ open, 2021-07, Vol.11 (7), p.e048008-e048008

2021

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A practice model for interprofessional education in a first year anatomy class

Promoting deeper learning in pharmacy education using team-based learning

Lateral force microscope calibration using a modified atomic force microscope cantilever

Nationally hosted tax intervention : exploring South African students’ perceptions of its usefulness to develop pervasive skills

Wear of a single asperity using Lateral Force Microscopy

Field trips as an intervention to enhance pharmacy students’ positive perception of a management module in their final year: A pilot study

Giant pop-ins in nanoindented silicon and germanium caused by lateral cracking

Rapid Communications: Giant pop-ins in nanoindented silicon and germanium caused by lateral cracking

Quantitative comparison of three calibration techniques for the lateral force microscope

Observed transition from linear to non-linear friction–load behavior using a lateral force microscope

Thusa Phase II: The design of a nutrition intervention education programme

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

Quantifying the Accuracy of a Diagnostic Test or Marker

Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

Sample size for binary logistic prediction models: Beyond events per variable criteria

STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

Beyond Diagnostic Accuracy: The Clinical Utility of Diagnostic Tests

A guide to systematic review and meta-analysis of prediction model performance

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

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