activity
20222024
most citedDevelopment of the ChatGPT, Generative Artificial Intelligence and Natural Large Language Models for Accountable Reporting and Use (CANGARU) Guidelines

15 citations · 41 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG202414 cited

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance

Ben Van Calster, Gary S. Collins, Andrew J. Vickers +11

A myriad of measures to illustrate performance of predictive artificial intelligence (AI) models have been proposed in the literature. Selecting appropriate performance measures is…

stat.ME20241 cited

Extended sample size calculations for evaluation of prediction models using a threshold for classification

Rebecca Whittle, Joie Ensor, Lucinda Archer +10

When evaluating the performance of a model for individualised risk prediction, the sample size needs to be large enough to precisely estimate the performance measures of interest.…

cs.AI202315 cited

Development of the ChatGPT, Generative Artificial Intelligence and Natural Large Language Models for Accountable Reporting and Use (CANGARU) Guidelines

Giovanni E. Cacciamani, Michael B. Eppler, Conner Ganjavi +4

The swift progress and ubiquitous adoption of Generative AI (GAI), Generative Pre-trained Transformers (GPTs), and large language models (LLMs) like ChatGPT, have spurred queries a…

stat.ME202211 cited

Minimum Sample Size for Developing a Multivariable Prediction Model using Multinomial Logistic Regression

Alexander Pate, Richard D Riley, Gary S Collins +4

Multinomial logistic regression models allow one to predict the risk of a categorical outcome with more than 2 categories. When developing such a model, researchers should ensure t…