Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Search results (62)

« Back to Publications

Substantial international variation in the cost of blood group and save and crossmatch: A systematic review.

Fabiano G. et al, (2026), Br J Haematol

Acute upper gastrointestinal bleeding in the UK: 2022 audit update.

Nigam GB. et al, (2025), Gut

Head-to-head comparison of the RMI and ADNEX models to estimate the risk of ovarian malignancy: a systematic review and meta-analysis of external validation studies.

Barreñada L. et al, (2025), BMJ Open, 15

Peer review reports of randomized controlled trials in oncology can be short and superficial.

Logullo P. et al, (2025), J Clin Epidemiol, 185

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation.

Collins GS. et al, (2025), Ewha Med J, 48

Development of a multicentre cohort study to understand the role of MRI and ultrasound in the diagnosis of acute haematogenous bone and joint infection in children (the PIC Bone study) : a study protocol.

Nogaro M-C. et al, (2025), Bone Jt Open, 6, 677 - 684

Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review.

Tsegaye B. et al, (2025), J Clin Epidemiol, 180

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods.

Moons KGM. et al, (2025), BMJ, 388

Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches.

Riley RD. et al, (2025), BMJ, 388

Evaluation of comorbidity measures for predicting mortality and revision surgery after elective primary shoulder replacement surgery based on data from the National Joint Registry and Hospital Episode Statistics for England: population based cohort study.

Valsamis EM. et al, (2025), BMJ Med, 4

Head-to-head comparison of the RMI and ADNEX models to estimate the risk of ovarian malignancy: systematic review and meta-analysis of external validation studies

Barreñada L. et al, (2024)

Calculating the power of a planned individual participant data meta-analysis to examine prognostic factor effects for a binary outcome.

Whittle R. et al, (2024), Res Synth Methods, 15, 905 - 916

Artificial intelligence in peri-operative prediction model research: are we there yet?

Shah A. and Dhiman P., (2024), Anaesthesia, 79, 1017 - 1022

SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models.

Andaur Navarro CL. et al, (2024), J Clin Epidemiol, 170

Prediction model protocols indicate better adherence to recommended guidelines for study conduct and reporting.

Dhiman P. et al, (2024), J Clin Epidemiol, 169

Load More

1
2
3
4
5