Sign in

TRIPOD Statement

@tripodstatement.bsky.social
513 followers 5 following 41 posts

Reporting guidelines for clinical prediction (including for AI/ML) TRIPOD-2015 (tinyurl.com/ywc8m624) TRIPOD+AI (tinyurl.com/4s8f3ze6) TRIPOD-LLM (tinyurl.com/y4ekxxre) Visit -> www.tripod-statement.org

PostsRepliesMedia
TRIPOD Statement @tripodstatement.bsky.social · 12/02/2026
We are setting out to develop some new recommendations (TRIPOD-CODE) to provide guidance on reporting the availability and structure of code for predictive AI healthcare tools Watch this space, and read the protocol here link.springer.com/article/10.1... #transparency #code #reproducibility
0155
TRIPOD Statement @tripodstatement.bsky.social · 27/01/2026
Looking to assess adherence to TRIPOD+AI? We have a new #openaccess paper in @jclinepi.bsky.social "Adherence to TRIPOD+AI guideline: an updated reporting assessment tool" --> linkinghub.elsevier.com/retrieve/pii... #machinelearning #AI #metascience #transparency
042
TRIPOD Statement @tripodstatement.bsky.social · 15/12/2025
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 (and should not) be reported and why --> tinyurl.com/bdehp3ht #predictiveAI #machinelearning #digitalhealth #transparency
011
TRIPOD Statement @tripodstatement.bsky.social · 25/04/2025
Complete and transparent reporting aids critical and assessing risk of bias in #predictiveAI. TRIPOD+AI and PROBAST+AI are key tools to improve #AI research in healthcare TRIPOD+AI -> tinyurl.com/39pz3rfd PROBAST+AI -> tinyurl.com/yt8vrvrf #Digitalhealth #healthcareAI #machinelearning
032
TRIPOD Statement @tripodstatement.bsky.social · 25/03/2025
The new PROBAST+AI tool to assess quality & risk of bias of #predictive#AI models in healthcare is predicated on good reporting, i.e., by following the TRIPOD+AI guidance PROBAST+AI www.bmj.com/content/388/... TRIPOD+AI www.bmj.com/content/385/... #MLSky #StatsSky #digitalhealth #machinelearning
011
TRIPOD Statement @tripodstatement.bsky.social · 13/02/2025
TRIPOD+AI (Expanded E&E): "If uncertainty intervals for individual prediction model outputs have been presented then provide details on how this was done" (www.bmj.com/content/385/...) 👇This new paper provides insight into uncertainty of risk estimate on decision making www.bmj.com/content/388/...
088
TRIPOD Statement @tripodstatement.bsky.social · 07/02/2025
Underpinning the FUTURE-AI recommendations 👇 is transparency Reporting guidelines like TRIPOD+AI are essential to ensure all key details are completely & transparently reported Get them here -> www.bmj.com/content/385/... #predictiveAI #machinelearning #trustworthyAI #healthcareAI #digitalhealth
031
TRIPOD Statement @tripodstatement.bsky.social · 25/01/2025
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 😁 www.bmj.com/content/385/... #MLsky #StatsSky #MedSky #transparency #AI
063
TRIPOD Statement @tripodstatement.bsky.social · 13/01/2025
TRIPOD+AI (www.bmj.com/content/385/...) ask authors to 'Report model performance estimates with confidence intervals' This preprint by STRATOS provides a critical overview of the properties of 32 commonly reported performance measures -> arxiv.org/abs/2412.10288 #MLSky #StatsSky #machinelearning
011
TRIPOD Statement @tripodstatement.bsky.social · 08/01/2025
Great to see "TRIPOD+AI and DECIDE-AI are the highest quality guidelines with respect to rigor of development and the involvement of the stakeholders" 😄 in academic.oup.com/jamiaopen/ar... Get TRIPOD+AI from www.bmj.com/content/385/... #MLSky #StatsSky #MedSky
1166
TRIPOD Statement @tripodstatement.bsky.social · 08/01/2025
We have a NEW PAPER in @naturemedicine.bsky.social on reporting recommendations for addressing the unique challenges of #largelanguagemodels (LLMs) in biomedical applications www.nature.com/articles/s41... #MLSky #StatsSky #medSky #AISky #artificialintelligence #generativeAI #transparency
1288
TRIPOD Statement @tripodstatement.bsky.social · 24/12/2024
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. Ensure your study is completely reported by following TRIPOD+AI bmj.com/content/385/... #AI #StatsSky #MLSky
041
TRIPOD Statement @tripodstatement.bsky.social · 13/12/2024
When we developed TRIPOD+AI for reporting clinical prediction models, we introduced an #openscience section to facilitate transparency and reproducibility asking authors to describe protocol, code, data availability www.bmj.com/content/385/... #MLSky #machinelearning #StatsSky #AI #reproducibility
0165
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
We have a website www.tripod-statement.org where more information can be found including translations - we will be uploading French and Chinese translations of TRIPOD+AI soon. /end (for now 😉)
011
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Protocol development is a crucial in mapping out any research study. It provides key details on the rationale, objectives, design, data collection, analysis methods & dissemination plans before a piece of research is conducted, TRIPOD-P (in preparation) will provide guidance tinyurl.com/53pe46wh
131
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Large language models and #generativeAI are making a huge impact in healthcare and beyond, so we have developed TRIPOD-LLM to provide recommendations (will be published soon, but currently available as a preprint) tinyurl.com/bdhjv4hj +website tripod-llm.vercel.app
111
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Clear and informative reporting of journal & conference abstracts is essential to help readers and reviewers identify potentially relevant studies and decide whether to read the full text, so we developed TRIPOD-Abstracts to provide reporting recommendations tinyurl.com/52j8sad8
100
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
An important aspect of systematic reviews is risk of bias assessment, so members of the TRIPOD Initiative also developed the PROBAST tool tinyurl.com/4x9a8b4z (tool) tinyurl.com/3e6kkekt (guidance) An update for #machinelearing models (PROBAST+AI) will appear soon!
111
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
With the large and growing number of prediction models, systematic reviews to evaluate and summarise the overall evidence available are important, so we developed TRIPOD-SRMA to provide guidance on reporting these studies tinyurl.com/33ffsj9k #evidencesynthesis #systematicreviews
193
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Accompanying the TRIPOD Cluster is a 38 page explanation and elaboration paper (containing 213 references) which provides examples of good reporting and methodological insights into developing and validating clinical prediction models with clustered data. tinyurl.com/2kvvr4f9
121
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
If you are developing models using data from multiple centres, locations, or different studies. Accounting for clustering can be important to capture and explore heterogeneity in prediction model performance, so we developed TRIPOD-Cluster to guide the reporting. tinyurl.com/4bks4xmd
121
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
An overview on how and why TRIPOD+AI was developed can by found in this short piece by lead author @gscollins.bsky.social tinyurl.com/57dknawu
112
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
In April 2024, we updated TRIPOD to reflect methodological advances (including sample size, #fairness, #openscience) and to make it agnostic to modelling approach, and cater for #machinelearning methods (we called this TRIPOD+AI). tinyurl.com/2kc39b4s
111
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Accompanying the 2015 TRIPOD guideline is a detailed 73 page explanation and elaboration paper (containing 531 references) providing examples of good reporting and methodological insights into developing and validating clinical prediction models. tinyurl.com/29k7a5wm
100
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
...and to aid dissemination across different clinical areas we published the guidance simultaneously in 11 journals
100
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
Our first guideline led by @gscollins.bsky.social, Carl Moons, Hans Reitsma & Doug Altman was published in 2015 and provides recommendations for clinical prediction models (primarily regression based models). This made an impact and is widely used with ~9000 citations 🎉 tinyurl.com/3mbk7sv4
130
TRIPOD Statement @tripodstatement.bsky.social · 23/11/2024
We've made the move across...so here’s a little thread introducing the various TRIPOD reporting guidelines to provide standards for #transparency and completeness of clinical prediction models to facilitate #reproducibility and guide #openscience #MLSky #StatsSky #statistics #academia #EpiSky
2106
TRIPOD Statement @tripodstatement.bsky.social · 19/11/2024
Our latest recommendations for reporting #AI/#machinelearning prediction model studies in healthcare are available in the @bmj.com bmj.com/content/385/... Don't forget the further guidance for each reporting recommendation in the supplementary material #MLSky #statsSky #reportingstandards
42815