Top Tweets for #ML4HC
Together with @ValentinDeBort1 we co-advised @RenzoSoatto, Anders Hoel, Greycen Ren & Shorna Alam at a #ML4HC course project that got accepted at @icmlconf!
CountsDiff:A diffusion model on the natural numbers for generation & imputation of count-based data
https://t.co/U9HOVg5kUQ
Last week, Iñigo Urteaga (@Ikerbasque Research Fellow), Santiago Mazuelas (@Ikerbasque Research Associate), and Lucia Filippozzi, (PhD Student), attended the “Machine Learning for Healthcare” congress 🧠🩺.
#ML4HC
Really need to see this being taken more seriously by folks working in this space, and for folks who are users of the tools #AIEthics #ML4HC #MedTwitter
Large language models propagate race-based medicine https://t.co/JxWVmBFmhu #artificialintelligence #llms #racism
Check out this set of job postings @SFU for #ethics #bioethics projects, including #HealthAI #ML4HC opportunities!
https://t.co/eAEJ8b1P6K
Want to hear what youth have to say about #AIEthics regarding #HealthAI #ML4HC ?
Come and join us virtually for #Bioethics Grand Rounds @SickKidsNews this Thursday at 12pm
Register here: https://t.co/oEX0LPRGnn
Excited to give a talk soon at #ML4HC! I promise to talk about #emmanueltheemu and its relevance to interpretability. "Don’t do it Emmanuel! How to stop worrying about interpretability, and start making progress"
Enjoying watching talks from #ML4HC, we had 3 short talks on upcoming work on #AI audits, datasets and evidence standards👇
@uhbtrust @UHBResearch @unibirm_MDS
"Optimal reporting of studies is crucial to ensure the results can be used to inform policy decisions"
In "Generating evidence for #ArtificialIntelligence based medical devices" (https://t.co/cHDysN9Vms) by @WHO
Great to see reporting & @EQUATORNetwork mentioned
#ML4HC
Make sure your (machine learning/statistical) prediction model paper is comprehensively & transparently reported by using the TRIPOD Statement
-> https://t.co/TtB7m3FMZ7 (Intro)
-> https://t.co/xjVox5SzrA (Explanation/Examples)
#StatsTwitter #ML4HC #MedTwitter #MachineLearning
"Missing data is poorly handled and reported in prediction model studies using #machinelearning: a literature review" --> https://t.co/8qXU5GTy9F
Looks like this will feed into and inform @TRIPODStatement-AI --> https://t.co/a1oFJRj4k4
#mltwitter #statstwitter #ML4HC
Seeing more reviews 👇looking at reporting (and consequences of poor reporting on risk of bias) of #machinelearning and #AI clinical prediction models.
--> guidance for reporting in preparation (TRIPOD-AI) (https://t.co/kfkREtPqmp)
#statstwitter #ML4HC @TRIPODStatement
Improving the reporting of #machinelearning prediction models.
Round 2 of the TRIPOD-AI Delphi consensus survey will open in a couple of weeks. DM me if you didn't participate in the round 1 & want to participate in round 2.
#statstwitter #medtwitter #ML4HC @EQUATORNetwork
We often say that #children are the future, but when we imagine the future of #healthcare with #ArtificialIntelligence, are the voices of children and #youth included in that vision?
https://t.co/lVwCaLntPD
@IAmSamFin Thanks for the reply Sam!
I didn’t know that, still waiting on my application to access MIMIC.
To anyone reading this, yes MIMIC is public, but you still have to complete a CITI data request certification and apply for access with MIT.
#ML4HC
Excellent paper. And let’s not go releasing medical GPT-2 models just yet... (other than those trained on public data)
Microsoft Word - beyond_interpretability_13.docx https://t.co/VnzenxxVJz #ai #machinelearning #artificialintelligence #ML4HC #FATML via @Miles_Brundage
Come work with one of the best minds in #ml4hc Danica Xiao at @IQVIA_global. Hiring machine learning scientists all over the globe. #AIJobs #iqvia https://t.co/akkAiqluuX
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