DNA methylation-based predictors of health: applications and statistical considerations
DNA methylation data have become a valuable source of information for biomarker
development, because, unlike static genetic risk estimates, DNA methylation varies …
development, because, unlike static genetic risk estimates, DNA methylation varies …
A scoping review of machine learning in psychotherapy research
Abstract Machine learning (ML) offers robust statistical and probabilistic techniques that can
help to make sense of large amounts of data. This scoping review paper aims to broadly …
help to make sense of large amounts of data. This scoping review paper aims to broadly …
COVID-19 vaccination intention in the UK: results from the COVID-19 vaccination acceptability study (CoVAccS), a nationally representative cross-sectional survey
To investigate factors associated with intention to be vaccinated against COVID-19 we
conducted a cross-sectional survey of 1,500 UK adults, recruited from an existing online …
conducted a cross-sectional survey of 1,500 UK adults, recruited from an existing online …
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 …
Minimum sample size for external validation of a clinical prediction model with a binary outcome
In prediction model research, external validation is needed to examine an existing model's
performance using data independent to that for model development. Current external …
performance using data independent to that for model development. Current external …
PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration
KGM Moons, RF Wolff, RD Riley, PF Whiting… - Annals of internal …, 2019 - acpjournals.org
Prediction models in health care use predictors to estimate for an individual the probability
that a condition or disease is already present (diagnostic model) or will occur in the future …
that a condition or disease is already present (diagnostic model) or will occur in the future …
Minimum sample size for developing a multivariable prediction model: PART II‐binary and time‐to‐event outcomes
When designing a study to develop a new prediction model with binary or time‐to‐event
outcomes, researchers should ensure their sample size is adequate in terms of the number …
outcomes, researchers should ensure their sample size is adequate in terms of the number …
A checklist for statistical assessment of medical papers (the CHAMP statement): explanation and elaboration
Misuse of statistics in medical and sports science research is common and may lead to
detrimental consequences to healthcare. Many authors, editors and peer reviewers of …
detrimental consequences to healthcare. Many authors, editors and peer reviewers of …
[HTML][HTML] Development and reporting of prediction models: guidance for authors from editors of respiratory, sleep, and critical care journals
DE Leisman, MO Harhay, DJ Lederer… - Critical care …, 2020 - journals.lww.com
Prediction models aim to use available data to predict a health state or outcome that has not
yet been observed. Prediction is primarily relevant to clinical practice, but is also used in …
yet been observed. Prediction is primarily relevant to clinical practice, but is also used in …
Intratumoral heterogeneity and clonal evolution in liver cancer
Clonal evolution of a tumor ecosystem depends on different selection pressures that are
principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR …
principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR …