Joined September 2013
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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 ๐Ÿ™ tinyurl.com/4kv7pb3m #transparency #AI
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TRIPODStatement retweeted
We are setting out to develop some new recommendations (TRIPOD-CODE) to provide guidance on reporting the availability & structure of code for predictive AI healthcare tools Watch this space & read the protocol here link.springer.com/article/10โ€ฆ #transparency #code #reproducibility
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In TRIPOD AI (tinyurl.com/4s6pmz5d) we ask authors to report the performance of their #AI model. This new authoritative position paper provides clarity on what measures should be reported and why --> tinyurl.com/bdehp3ht #predictiveAI #machinelearning #digitalhealth
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TRIPODStatement retweeted
19 Sep 2025
Thank you @Anaes_Journal for the incredible opportunity to share our work! Grateful to the GRAITE-USRA steering group, all Delphi experts & endorsing societies for their invaluable contributions, insights & support. A true multidisciplinary effort to improve AI reporting in RA ๐Ÿ™๐Ÿผ
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1 Aug 2025
Attention #AI researchers, clinicians, patients, editors, publishers, & beyond๐Ÿ‘‹ Just in ๐Ÿ–จ๏ธ - the #CHART reporting guideline โœ… for studies evaluating #genAI models like #ChatGPT & other #LLMs for health advice Statement: ๐Ÿ‘‰bit.ly/CHARTbmjmed ๐Ÿ‘‰bit.ly/CHARTbjs ๐Ÿ‘‰bit.ly/CHARTbmc ๐Ÿ‘‰bit.ly/CHARTjamao ๐Ÿ‘‰bit.ly/CHARTannfam ๐Ÿ‘‰bit.ly/CHARTartmed E&E: ๐Ÿ‘‰bit.ly/CHARTbmj Published in @BMJMedicine @BJSurgery @JAMANetworkOpen @BMCMedicine @AnnFamMed & Art Med @GuyattGH | @GSCollins | @Cacciamani_MD | @CLaineMD | @AFlanagin | @thirumasu | @AlfonsoIorio | @juliomayol | @nliulab | @riazagha | @DrXiaoLiu | @SunjayaMD | @drnipunverma | @YJeremyNg | @mike_mitt | @meerpohl | @Tfeend | @eloder | @HelenFrankish | @LoebStacy | @tylermckechnie | @YungLeeMDMPH @EQUATORNetwork
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NEW PAPER in @bmj_latest "Dealing with continuous variables and modelling non-linear associations in healthcare data: practical guide" --> bmj.com/content/390/bmj-2024โ€ฆ #methodologymatters
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TRIPODStatement retweeted
๐ŸŒ Advancing international partnership for governing generative #AI (#GenAI) models in #medicine and #healthcare. We introduce POLARIS-GM initiative: a scenario-based, consensus-driven framework for GenAI #governance and #regulation. @NatureMedicine nature.com/articles/s41591-0โ€ฆ
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TRIPODStatement retweeted
NEW PREPRINT "Critical Appraisal of Fairness Metrics in Clinical Predictive AI" -> arxiv.org/abs/2506.17035 We identified 62 fairness metrics (& growing) - unsurprisingly it's all a bit of a mess...with most metrics not fit for purpose #predictiveAI #fairness #machinelearning
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Item 10 of the TRIPOD AI asks (bmj.com/content/385/bmj-2023โ€ฆ) "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 ๐Ÿ‘‡
**New Lancet DH paper "Importance of sample size on the quality & utility of AI-based prediction models for healthcare" - for broad audience - why inadequate SS harms model training, evaluation & performance - pushback to claims SS irrelevant to #AI ๐Ÿ‘‡ tinyurl.com/yrje52fn
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Who uses TRIPOD-AI? ๐Ÿ‘ฉ๐Ÿ”ฌ Researchers designing models ๐Ÿ‘จโš•๏ธ Clinicians evaluating tools ๐Ÿ‘ฉ๐Ÿ’ป Developers building algorithms ๐Ÿ“‹ Journals & peer reviewers A shared framework for responsible innovation. ๐Ÿค #DigitalHealth #HealthcareAI
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Letโ€™s raise the standard! Adopting TRIPOD AI means advancing equitable, accountable AI ready for clinics. Check guidelines: tripod-statement.org ๐Ÿ“– Together, we can ensure AI serves patients first. #OpenScience #AIforGood

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TRIPODStatement retweeted
15 Apr 2025
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 @GSCollins bmj.com/content/389/bmj.r718โ€ฆ
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TRIPODStatement retweeted
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 ๐Ÿ™ tinyurl.com/4kv7pb3m #transparency #AI
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TRIPODStatement retweeted
Underpinning the FUTURE-AI recommendations ๐Ÿ‘‡ is transparency TRIPOD AI recommendations are essential to ensure all key details are completely & transparently reported bmj.com/content/385/bmj-2023โ€ฆ #predictiveAI #machinelearning #trustworthyAI #healthcareAI #digitalhealth
5 Feb 2025
This paper describes the FUTURE-AI framework, which provides guidance for the development and deployment of trustworthy AI tools in healthcare, @KarimLekadir and colleagues bmj.com/content/388/bmj-2024โ€ฆ
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