Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Prognostic models that aim to improve the prediction of clinical events, individualized
treatment and decision-making are increasingly being developed and published. However …

Introduction The Transparent Reporting of a multivariable prediction model of Individual
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …

Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

Background The assessment of calibration performance of risk prediction models based on
regression or more flexible machine learning algorithms receives little attention. Main text …

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 …

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 …

For more on theTRIPOD statement see https://www. tripodstatement. org technology, and
intelligent monitoring. Behind the digital health revolution are also methodological …

Prognostic factors are associated with the risk of future health outcomes in individuals with a
particular health condition or some clinical start point (eg, a particular diagnosis). Research …

Topical products, widely used to manage skin conditions, have evolved from simple potions
to sophisticated delivery systems. Their development has been facilitated by advances in …