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Reposted by TRIPOD Statement

Gary Collins @gscollins.bsky.social · 26d

NEW PAPER "The STARD-AI reporting guideline for diagnostic accuracy studies using #artificialintelligence"

--> www.nature.com/articles/s41...

#machinelearning #MLsky #statssky #digitalhealth #transparency

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Reposted by TRIPOD Statement

Gary Collins @gscollins.bsky.social · Jul 16

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

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Reposted by TRIPOD Statement

Gary Collins @gscollins.bsky.social · Jun 26

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

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Reposted by TRIPOD Statement

Journal of Clinical Epidemiology @jclinepi.bsky.social · May 25

Maternal early warning scores shown to be methodologically weak and at high risk of bias - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...

Maternal early warning scores shown to be methodologically weak and at high risk of bias

To systematically review and critically appraise the methodology of developing Modified Obstetric Early Warning Scores (MOEWSs).

www.jclinepi.com

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TRIPOD Statement @tripodstatement.bsky.social · Jun 2

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 👇

Richard Riley (R²) @richarddriley.bsky.social · Jun 2

**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

Importance of sample size on the quality and utility of AI-based prediction models for healthcare

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. On…

www.sciencedirect.com

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Reposted by TRIPOD Statement

Richard Riley (R²) @richarddriley.bsky.social · Jun 2

**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

Importance of sample size on the quality and utility of AI-based prediction models for healthcare

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. On…

www.sciencedirect.com

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TRIPOD Statement @tripodstatement.bsky.social · May 20

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

Tripod statement

tripod-statement.org

TRIPOD Statement @tripodstatement.bsky.social · May 20

Who uses TRIPOD-AI?
👩🔬 Researchers designing models
👨⚕️ Clinicians evaluating tools
👩💻 Developers building algorithms
📋 Journals & peer reviewers
A shared framework for responsible innovation. 🤝 #DigitalHealth #HealthcareAI

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TRIPOD Statement @tripodstatement.bsky.social · May 20

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

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TRIPOD Statement @tripodstatement.bsky.social · May 20

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

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TRIPOD Statement @tripodstatement.bsky.social · May 20

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

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting recommendations for studie...

bmj.com

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TRIPOD Statement @tripodstatement.bsky.social · Apr 25

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

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Reposted by TRIPOD Statement

EQUATOR Network @equatornetwork.bsky.social · Apr 11

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...

UK EQUATOR Centre Publication School

Fit for purpose: The secrets of success in writing, publishing, and disseminating research articles

bit.ly

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Reposted by TRIPOD Statement

EQUATOR Network @equatornetwork.bsky.social · Apr 11

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...

UK EQUATOR Centre Publication School

Fit for purpose: The secrets of success in writing, publishing, and disseminating research articles

bit.ly

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TRIPOD Statement @tripodstatement.bsky.social · Mar 25

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

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Reposted by TRIPOD Statement

Richard Riley (R²) @richarddriley.bsky.social · Mar 24

*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/...

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods

The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies....

www.bmj.com

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Reposted by TRIPOD Statement

Gary Collins @gscollins.bsky.social · Mar 24

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

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Reposted by TRIPOD Statement

TRIPOD Statement @tripodstatement.bsky.social · Jan 25

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

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Reposted by TRIPOD Statement

SESSTIM @sesstim.bsky.social · Mar 13

[ #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)

💻https://sesstim.univ-amu.fr/fr/content/webinar-quantim-gary-collins

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Reposted by TRIPOD Statement

TRIPOD Statement @tripodstatement.bsky.social · Feb 13

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/...

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TRIPOD Statement @tripodstatement.bsky.social · Feb 13

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/...

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Reposted by TRIPOD Statement

Jason Moore @moorejh.bsky.social · Feb 7

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare www.bmj.com/content/388/... #artificialintelligence #healthcare #bioinformatics #ethics #trust

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. This paper describes the FUTURE-AI f...

www.bmj.com

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TRIPOD Statement @tripodstatement.bsky.social · Feb 7

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

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Reposted by TRIPOD Statement

Gary Collins @gscollins.bsky.social · Feb 5

NEW PAPER in @bmj.com "FUTURE-AI: international consensus guideline for trustworthy and deployable #artificialintelligence in healthcare" from design, development, validation to regulation, deployment & monitoring

www.bmj.com/content/388/...

#StatsSky #MLSky #MedSky

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TRIPOD Statement @tripodstatement.bsky.social · Jan 25

👇 Item 10 of TRIPOD+AI

"Explain how the study size was arrived at (separately for development and evaluation), and justify that the study size was sufficient to answer the research question. Include details of any sample size calculation"

www.bmj.com/content/385/...

#MLSky #StatsSky

Journal of Clinical Epidemiology @jclinepi.bsky.social · Jan 23

Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...

Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review

Having a sufficient sample size is crucial when developing a clinical prediction model. We reviewed details of sample size in studies developing prediction models for binary outcomes using machine lea...

www.jclinepi.com

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