Traumatic brain injury: progress and challenges in prevention, clinical care, and research
Executive summary Traumatic brain injury (TBI) has the highest incidence of all common
neurological disorders, and poses a substantial public health burden. TBI is increasingly …
neurological disorders, and poses a substantial public health burden. TBI is increasingly …
Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare
Abstract Machine learning (ML) and artificial intelligence (AI) algorithms have the potential to
derive insights from clinical data and improve patient outcomes. However, these highly …
derive insights from clinical data and improve patient outcomes. However, these highly …
Calibration: the Achilles heel of predictive analytics
Background The assessment of calibration performance of risk prediction models based on
regression or more flexible machine learning algorithms receives little attention. Main text …
regression or more flexible machine learning algorithms receives little attention. Main text …
Calculating the sample size required for developing a clinical prediction model
Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or
prognosis in healthcare. Hundreds of prediction models are published in the medical …
prognosis in healthcare. Hundreds of prediction models are published in the medical …
Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology
Objective To provide an overview and critical appraisal of early warning scores for adult
hospital patients. Design Systematic review. Data sources Medline, CINAHL, PsycInfo, and …
hospital patients. Design Systematic review. Data sources Medline, CINAHL, PsycInfo, and …
Worldwide access to treatment for end-stage kidney disease: a systematic review
Background End-stage kidney disease is a leading cause of morbidity and mortality
worldwide. Prevalence of the disease and worldwide use of renal replacement therapy …
worldwide. Prevalence of the disease and worldwide use of renal replacement therapy …
Prediction models for cardiovascular disease risk in the general population: systematic review
Objective To provide an overview of prediction models for risk of cardiovascular disease
(CVD) in the general population. Design Systematic review. Data sources Medline and …
(CVD) in the general population. Design Systematic review. Data sources Medline and …
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration
KGM Moons, DG Altman, JB Reitsma… - Annals of internal …, 2015 - acpjournals.org
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the …
Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the …
A calibration hierarchy for risk models was defined: from utopia to empirical data
B Van Calster, D Nieboer, Y Vergouwe… - Journal of clinical …, 2016 - Elsevier
Objective Calibrated risk models are vital for valid decision support. We define four levels of
calibration and describe implications for model development and external validation of …
calibration and describe implications for model development and external validation of …
Towards better clinical prediction models: seven steps for development and an ABCD for validation
EW Steyerberg, Y Vergouwe - European heart journal, 2014 - academic.oup.com
Clinical prediction models provide risk estimates for the presence of disease (diagnosis) or
an event in the future course of disease (prognosis) for individual patients. Although …
an event in the future course of disease (prognosis) for individual patients. Although …