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Prikvačeni tweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Friends, I’m giving a talk at this DC/policy focused meeting: https://www.academyhealth.org/page/2020-hdp-agenda … I’m looking for egs of tasteless
#AI/ML algorithmic research or poor implementations that could have harmful consequences, to highlight what they did wrong & what right might have looked like.Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
My obs: Many DL/CI/AI debates sparked by non-expert twitter provocateurs & core researchers feel the pressure to respond! Our productive scientists ought to be helping make research progress! Cur back & forth presents a hostile image often rehashing the same topic. Am I wrong?https://twitter.com/suchisaria/status/1216472057057333250 …
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This study’s caused a stir. My take: -regression to the mean is a common flaw in pre/post studies; this intervention was esp vulnerable b/c it selected patients at the peak. This could have been ~corrected for(even w/o RCT) -but has standard of care also improved sig over time?https://twitter.com/califf001/status/1216376922566873088 …
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Just noticed our cookbook shelf has one VERY odd resident! (Organized by our movers a year ago.)pic.twitter.com/04Sw3bcqwO
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This is no different than how other non-AI diagnostic/screening tests have been introduced before: analyze the safety and efficacy — ie, downstream consequences of over treatment and missed diagnosis before introducing a protocol that’s deployed at scalehttps://twitter.com/nikillinit/status/1213234080617304066 …
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This isn’t surprising. DL uses a class of models; I think of the rest as ML—learning frm small sample, correcting 4 bias, inferring causal effects... But at the height of DL fever, DL got branded as a separate field & known learning principles got reinvented w/ DNN in the titlehttps://twitter.com/ylecun/status/1209497021398343680 …
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If you love puzzles and decoding magic, and want to be entertained, visit the
@nytimes crossword constructor@davidkwong ‘s magic show. It is absolutely brilliant! Mind blown. (And, the perfect idea for a NYC date!)https://twitter.com/sacca/status/1205560463389388800 …
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Imagine discussing machine learning and medicine in Bermuda with other top researchers across informatics, policy, clinical translation, and ML. That's what this meeting is about! Abstracts due soon. If you have questions, send me a note.https://twitter.com/NEJM/status/1201667366477688832 …
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Suchi Saria proslijedio/la je Tweet
Finally, a paper on why "AI for good" is an empty phrase without a theory of change. What is "good" is never articulated in the rush to tech solutions, while alternative reforms are overlooked. Read
@benzevgreen's piece before it blows up at@NeurIPSConf https://www.benzevgreen.com/wp-content/uploads/2019/11/19-ai4sg.pdf …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Suchi Saria proslijedio/la je Tweet
Watch “Panel: How Connected Data Can Power a Learning Healthcare System” on
#Vimeo https://vimeo.com/372294350 Valuable point by@suchisaria: care providers should see the system improving their productivity, helping them do something better esp when already have lots of things to doHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Related: Published in Biostatistics this week, this article overviews learning methods that correct for statistical biases commonly observed when developing tools from real-world EHR data.https://academic.oup.com/biostatistics/advance-article/doi/10.1093/biostatistics/kxz041/5631850 …
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Nice paper by
@ravi_b_parikh et al. w/ examples disentangling social vs statistical bias & ideas for how (well-designed) AI/ML tools can help mitigate social bias: https://jamanetwork.com/journals/jama/fullarticle/2756196?guestaccesskey=7e4f05f9-7aad-470b-8cc8-b6f5b2553da0&utm_source=silverchair&utm_medium=email&utm_campaign=article_alert-jama&utm_content=olf&utm_term=112219&alert=article … We can't solve a problem we don't understand. To address bias, we need a cleaner taxonomy.pic.twitter.com/StEupNCQXO
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Suchi Saria proslijedio/la je Tweet
Why would we use
#ML to predict risk of kidney injury based on contrast exposure during stent placement? Because the relationship is complex. Non-linear and nuanced. We can individualize the predictions. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2755869 …@JAMANetworkOpen@jbmortazavipic.twitter.com/BWyPsInG1f
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Suchi Saria proslijedio/la je Tweet
Highly recommend checking out this issue.
@suchisaria and I discuss problems w/ differing training and deployment conditions, and how causality gives us a language/tools to express and identify the problem, and tools to develop new robust algorithms. https://academic.oup.com/biostatistics/advance-article/doi/10.1093/biostatistics/kxz041/5631850 …https://twitter.com/sherrirose/status/1196779501356769281 …
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Suchi Saria proslijedio/la je Tweet
As the editors of
@biostatistics,@drizopoulos and I are thrilled to share this free access multidisciplinary collection of commentaries on machine learning for causal inference. All 5 pieces are linked in our editorial about the series: https://academic.oup.com/biostatistics/advance-article/doi/10.1093/biostatistics/kxz045/5631847 …pic.twitter.com/zWbMOjT8Na
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Suchi Saria proslijedio/la je Tweet
Today is a tipping point for value-based care in
#NC.@AtriumHealth and@NovantHealth are now part of#BluePremier, our value-based program that holds health systems and@BlueCrossNC jointly accountable for better health outcomes and lower costs. http://bit.ly/2QaTtnP pic.twitter.com/tgPxibwC3r
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Suchi Saria proslijedio/la je Tweet
Excellent HBR article citing brilliant
@suchisaria who I’d cite too (& who’s work I only partly understand) -#AI#radiology should consider some of this. Cc:@janbeger@FelipeKitamura@alexandrecadrin@judywawira@DrGMcGinty@quantrad@RasuShresthahttps://twitter.com/MashZahid/status/1193975859943743489 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Suchi Saria proslijedio/la je Tweet
Here's the thing. 1/ The perception of Google culture is that no-one curbs the curiosity of engineers Google can sign a BAA, but they have to convince people that they actually have controls in place to ensure that the data is only being used for the purposes of the agreementhttps://twitter.com/chrissyfarr/status/1194058886279385090 …
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Aww, thx! My favorite meetings are when the discussants & speakers prior to me motivate new talk threads. Vincent Liu from
@aboutKP led to my creating of this slide asking when do we need high quality models vs when are simple rule-based/epic-style predictive systems enough?https://twitter.com/DrAmithaMD/status/1189604409367502849 …
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