Supervised machine learning: a brief primer
Abstract Machine learning is increasingly used in mental health research and has the
potential to advance our understanding of how to characterize, predict, and treat mental …
potential to advance our understanding of how to characterize, predict, and treat mental …
[HTML][HTML] Criteria for the translation of radiomics into clinically useful tests
EP Huang, JPB O'Connor, LM McShane… - Nature reviews Clinical …, 2023 - nature.com
Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations
Abstract Background Directed acyclic graphs (DAGs) are an increasingly popular approach
for identifying confounding variables that require conditioning when estimating causal …
for identifying confounding variables that require conditioning when estimating causal …
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 …
[HTML][HTML] A brief review of random forests for water scientists and practitioners and their recent history in water resources
Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …
to gain prominence in water resources applications. However, existing applications are …
The 20-minute city: An equity analysis of Liverpool City Region
The 20-minute city has become a popular urban planning policy to support low-transport
neighbourhoods. Whilst meeting residents' needs in local neighbourhoods is not a new …
neighbourhoods. Whilst meeting residents' needs in local neighbourhoods is not a new …
[HTML][HTML] Behavioural intention to use autonomous vehicles: Systematic review and empirical extension
T Keszey - Transportation research part C: emerging technologies, 2020 - Elsevier
This study aims to enrich autonomous vehicle (AV) adoption research and practice by being
the first study to systematically review empirical studies on behavioural intention to use AVs …
the first study to systematically review empirical studies on behavioural intention to use AVs …
A deep learning based traffic crash severity prediction framework
Highway work zones are most vulnerable roadway segments for congestion and traffic
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
[HTML][HTML] State of the art in selection of variables and functional forms in multivariable analysis—outstanding issues
W Sauerbrei, A Perperoglou, M Schmid… - … and prognostic research, 2020 - Springer
Background How to select variables and identify functional forms for continuous variables is
a key concern when creating a multivariable model. Ad hoc 'traditional'approaches to …
a key concern when creating a multivariable model. Ad hoc 'traditional'approaches to …
Effectiveness of e-cigarettes as aids for smoking cessation: evidence from the PATH Study cohort, 2017–2019
Objective To assess the effectiveness of e-cigarettes in smoking cessation in the USA from
2017 to 2019, given the 2017 increase in high nicotine e-cigarette sales. Methods In 2017 …
2017 to 2019, given the 2017 increase in high nicotine e-cigarette sales. Methods In 2017 …