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2024 saw us publish TRIPOD+AI, a major update to the TRIPOD reporting guideline for studies developing/evaluating prediction models using #machinelearning and statistical methods bmj.com/content/385/bm… #AI #statstwitter #transparency

We have a NEW PAPER in Nature Medicine on reporting recommendations for addressing the unique challenges of #largelanguagemodels (LLMs) in biomedical applications nature.com/articles/s4159… #StatsTwitter #MedTwitter #artificialintelligence #generativeAI #transparency

TRIPOD-LLM is a checklist of items essential for good reporting of studies involving #LLMs for use in healthcare settings; a ‘living guideline’, it emphasizes transparency, human oversight & task-specific performance reporting. Danielle Bitterman, MD Brigham and Women's Hospital nature.com/articles/s4159…

TRIPOD-LLM is out! Check out our consensus guidelines for reporting #LLM research in biomedicine. TRIPOD-LLM is intended to be a living guideline to keep up with the rapid advances in #LLMs/Gen AI. Kudos to lead author jack gallifant

Paper: nature.com/articles/s4159… Interactive site to complete the checklist: tripod-llm.vercel.app

1/ 🌟 Exciting news for healthcare AI! The TRIPOD-LLM guideline sets new standards for reporting studies involving large language models (LLMs) in healthcare. A game-changer for transparency and reproducibility. Here’s a deep dive! 🧵👇 #AIinHealthcare #LLMs

10/ 🌐 Learn more and access the guideline here: nature.com/articles/s4159… Together, we can ensure AI advances responsibly, improving healthcare outcomes while minimizing risks. Let’s build a fair, transparent AI future! 🌟 #AI4Good

"Advances in LLMs have stretched regulatory structures to their limits, exposing a patchwork of solutions that do not fully encompass the nuances of these models." New EQUATOR Network guideline for biomedical applications of LLMs by Danielle Bitterman, MD et al: nature.com/articles/s4159…

A periodic reminder that if you are writing up your study developing/validating a #machinelearning clinical prediction model then make sure you are reporting all the necessary information by following the TRIPOD+AI standards 🙏 tinyurl.com/4kv7pb3m #transparency #AI

This paper describes the FUTURE-AI framework, which provides guidance for the development and deployment of trustworthy AI tools in healthcare, Karim Lekadir and colleagues bmj.com/content/388/bm…

Underpinning the FUTURE-AI recommendations 👇 is transparency TRIPOD+AI recommendations are essential to ensure all key details are completely & transparently reported bmj.com/content/385/bm… #predictiveAI #machinelearning #trustworthyAI #healthcareAI #digitalhealth

Reporting guidelines have become an essential instrument of scientific integrity. We need to make the leap from just producing reporting guidelines to helping researchers put them into practice, writes Gary Collins bmj.com/content/389/bm…

Item 10 of the TRIPOD+AI asks (bmj.com/content/385/bm…) "Explain how the study size was arrived at, and justify that the study size was sufficient to answer the research question. Include details of any sample size calculation" Here's why it's important 👇