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
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
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
End of year reminder: the TRIPOD+AI reporting guideline is reporting standard for all clinical prediction model studies, including those using machine learning and AI.
--> www.bmj.com/content/385/...
"The making of a statistician: Doug Altman" - just published in @bmj.com celebrating his 1 million citations and reflecting on his remarkable career and legacy. One of the most influential statisticians in modern medical research.
--> www.bmj.com/content/391/...
#BMJChristmas #methodologymatters
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
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
NEW PAPER: "Reporting guidelines for studies involving generative artificial intelligence applications: what do I use, and when?"
--> www.nature.com/articles/s41...
#HealthTech #ClinicalAI #MachineLearning #MedAI #AIinMedicine #TransparentAI #HealthInnovation #GenAI
NEW PAPER "The STARD-AI reporting guideline for diagnostic accuracy studies using #artificialintelligence"
--> www.nature.com/articles/s41...
#machinelearning #MLsky #statssky #digitalhealth #transparency
NEW PAPER in @bmj.com "Dealing with continuous variables and modelling non-linear associations in healthcare data: practical guide"
--> www.bmj.com/content/390/...
#methodologymatters #StatsSky #EpiSky
NEW PREPRINT "Critical Appraisal of Fairness Metrics in Clinical Predictive AI"
-> arxiv.org/abs/2506.17035
We identified 62 fairness metrics (and growing) - unsurprisingly it's all a bit of a mess...with most metrics not fit for purpose
#predictiveAI #fairness #machinelearning #StatsSky #MLSky
Maternal early warning scores shown to be methodologically weak and at high risk of bias - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...
Item 10 of the TRIPOD+AI asks
(www.bmj.com/content/385/...)
"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 👇
**New Lancet DH paper**
"Importance of sample size on the quality & utility of AI-based prediction models for healthcare"
- for broad audience
- explains why inadequate SS harms #AI model training, evaluation & performance
- pushback to claims SS irrelevant to AI research
👇
tinyurl.com/yrje52fn
Let’s raise the standards!
Adopting TRIPOD+AI means advancing equitable, accountable AI ready for clinics.
Check guidelines: tripod-statement.org 📖
Together, we can ensure AI serves patients first. #OpenScience #AIforGood
Who uses TRIPOD-AI?
👩🔬 Researchers designing models
👨⚕️ Clinicians evaluating tools
👩💻 Developers building algorithms
📋 Journals & peer reviewers
A shared framework for responsible innovation. 🤝 #DigitalHealth #HealthcareAI
Why TRIPOD-AI?
🔹 Ensures models can be replicated/validated
🔹 Builds trust with clinicians & patients
🔹 Reduces bias risks in outcomes
🔹 Bridges code to real-world care
Better reporting = better science for healthcare challenges. 🌍💡
#AIethics #MedEd
TRIPOD-AI’s pillars:
✅ Transparent data sources & preprocessing
✅ Full model architecture/training details
✅ Rigorous validation (internal/external)
✅ Ethics checks & bias mitigation
✅ Clear clinical impact
No more “black box” AI!
🔍 #EthicalAI #MachineLearning
A guideline to boost transparency in AI-driven medical prediction models! Evolved from TRIPOD, it ensures studies are reproducible, ethical, and clinically meaningful. Crucial for trustworthy #AI in healthcare.
Read the paper: bmj.com/content/385/...
#HealthTech
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
Early-career researchers and students in health research! Join the UK EQUATOR Centre's Publication School to learn how to plan, write, and publish excellent journal articles.
Date: Mondays, 23 June – 14 July 2025
Time: 9:30 – 13:30 GMT+1
Where: Online via Zoom
bit.ly/equatorpubsc...
Health researchers, have you ever wondered how to:
• Negotiate authorship
• Choose a journal
• Develop good writing habits
• Write each section of an article
• Revise your own writing
• Respond to peer review
The UK EQUATOR Centre's Publication School is here to help! bit.ly/equatorpubsc...
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
*NEW PAPER*
PROBAST+AI: an updated quality, risk of bias & applicability assessment tool for prediction models using regression or AI methods
PROBAST+AI consists of two distinct parts:
- model development (quality assessment tool)
- model evaluation (risk of bias tool)
www.bmj.com/content/388/...
NEW PAPER in the @bmj.com "PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or #artificialintelligence methods"
www.bmj.com/content/388/...
#StatsSky #MLSky #AI #MethodologyMatters
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
[ #Webinar ] D-8 until our next webinar! ⤵️
💬The importance of transparency in predictive AI: the role of reporting guidelines
🗣️ @gscollins.bsky.social (@ox.ac.uk)
💻sesstim.univ-amu.fr/fr/content/webinar-quant...
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/...
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/...
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare www.bmj.com/content/388/... #artificialintelligence #healthcare #bioinformatics #ethics #trust