<p><span>Clinical artificial intelligence (AI) joins a long list of technologies that promise to improve healthcare, but lack the evidence that it leads to valu

External validation is essential for assessing the generalisability and transportability of a clinical prediction model. A previous review of studies published in 2010 identified substantial deficienc...

Background Transparency and openness are core scientific values that enable independent verification of reported research results. The Transparency and Openness Promotion (TOP) Guidelines, first publi...

Background Despite endorsement by medical journals, reporting guidelines have only modestly affected reporting quality in healthcare research. We aimed to identify influences affecting whether authors...

Most original articles published in the medical literature report the results of multiple statistical tests. In a few simple cases, there is agreement on whether to adjust for the number of performed...

The models are designed to predict someone’s risk of diabetes or stroke. A few might already have been used on patients.

The open access movement was bold and promising, but ultimately disappointing. Now is the time to stop and call for a new way to make publishing work…

Exclusive: Charitable funder cites “inefficient and costly” system, promising transition for researchers

Methodological studies critically evaluate how health research is designed, conducted, analyzed, and reported. Despite their growing importance, currently, there is no reporting tailored to this type ...

UK will suffer lasting consequences from disrupted talent pipeline, say Mike Lockwood and James Wild

Open Access book by Luc Smits, Sander van Kuijk, and Laure Wynants: This open-access textbook offers a practical and comprehensive guide to developing, validating, and implementing clinical prediction...

Exclusive: Scale of redundancies revealed by RPN branded a “disaster” for UK research capacity

Clinical prediction models are often created using large routinely collected datasets. It is essential that prediction models are developed with appropriate data and methods and transparently reported...

Exclusive: Scale of redundancies revealed branded a “disaster” for UK research capacity

Incomplete reporting of research limits its usefulness and contributes to research waste. Numerous reporting guidelines have been developed to support complete and accurate reporting of healthcare res...

Large language models (LLMs) are emerging as powerful tools in healthcare, with a growing role in global health, particularly in low- and middle-income countries. This Perspective examines the current...

YouTube video by the Causal Inference Interest Group (CIIG)

When recruiting participants to a new study developing a clinical prediction model (CPM), sample size calculations are typically conducted before data collection based on sensible assumptions. This le...

Clinical prediction models are widely developed in the field of oncology, providing individualised risk estimates to aid diagnosis and prognosis. Machine learning methods are increasingly being used t...

With so little money to go round, the costs of competing for grants can exceed what the grants are worth. When that happens, nobody wins.

Numerous measures have been proposed to illustrate the performance of predictive artificial intelligence (AI) models. Selecting appropriate performance measures is essential for predictive AI models i...