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Jakob Steinfeldt proslijedio/la je Tweet
Want To Be AI-First? You Need To Be Data-First.https://www.forbes.com/sites/cognitiveworld/2020/01/30/want-to-be-ai-first-you-need-to-be-data-first/amp/?__twitter_impression=true …
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Jakob Steinfeldt proslijedio/la je Tweet
Neu auf unserem
#DMEA20#Newsblog
: Im Interview spricht @stefan_radatz von@CernerDE über die nächste Generation der Krankenhausinformationssysteme
#KIS#DigitalHealth#DMEA#GoldpartnerHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
Terminologien und Ontologien im Gesundheitswesen | HiGHmeducation https://lehre.highmed.org/Module/Modulangebot/Terminologien-und-Ontologien-im-Gesundheitswesen …
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Jakob Steinfeldt proslijedio/la je Tweet
Everyone wants to lead in AI, but the real work is in data architecture and engineering - it's time to get serious about building these foundations before we focus on models and algorithms! | Want To Be AI-First? You Need To Be Data-First. via
@forbeshttps://www.forbes.com/sites/cognitiveworld/2020/01/30/want-to-be-ai-first-you-need-to-be-data-first/#629a97bf3a43 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
Snomed: nCoV 840533007 Antigen of nCoV 840536004 Exposure to nCoV 840546002 Vaccination of nCoV 840534001 Antibody to nCoV 840535000 Disease caused by 840539006 Suspected disease caused by nCoV 840544004 DAS ist der Unterschied.
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Jakob Steinfeldt proslijedio/la je Tweet
Snomed




Die Patienten werden es danken. @_GLudewig@jensspahn@BMG_Bund@gmdsEV@AWMF_eVpic.twitter.com/yppVzjVcHI
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Jakob Steinfeldt proslijedio/la je Tweet
2021 rückt immer näher und somit auch die
#ePA. Wir sind uns einig: Sie sollte nicht nur eine Ablage-Dropbox sein. Sie steht und fällt mit der#Interoperabilität und Aufklärung der Patienten@MariaKlSchmeink@_GLudewig@DigitalNative88@marcelweigand@HashtagGesund@YandR_Berlinpic.twitter.com/EGgR2BQW9N
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Jakob Steinfeldt proslijedio/la je Tweet
There's "precision medicine" and "rabbit hole medicine" This report represents the latter. How to collect an avg $8,000/person, do many tests to get lots of abnormal findings (for more testing) and "health outcome and benefits were not measured" https://www.pnas.org/content/early/2020/01/23/1909378117 …
@PNASNewspic.twitter.com/VF6ZMpfarT
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Jakob Steinfeldt proslijedio/la je Tweet
Saw few tweets on pigeon-based classification of breast cancer (
@tunguz@hardmaru,@Dominic1King, & ML Reddit), which was published in 2015. I work with the legend himself@rml52! I thought for my 1st Twitter thread I'd go over the papers's main points & our current work! (1/11)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Jakob Steinfeldt proslijedio/la je Tweet
Terrific commentary by
@d_spiegel on ANDROMEDA study, raising serious questions about how Hardwicke and Ioannidis handled their survey of signatories to the 'end of significance' letter.https://medium.com/wintoncentre/andromeda-and-appalling-science-a-response-to-hardwicke-and-ioannidis-a79458efdba1 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
Kornia v0.2.0 is out ! We have introduced a new data augmentation module with strong GPU support, extended the set of color conversion algorithms, supporting GPU CI tests with
@PyTorch v1.4.0, and much more. Happy coding !pic.twitter.com/hizVSTL7CvPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
Ever wonder, are there any machine learning applications actually being used to care for patients in health care? If yes, check out our new review: https://emj.emg-health.com/wp-content/uploads/sites/2/2020/01/A-Path-for-Translation-of-Machine-Learning.....pdf … In it, we (
@Sehj_K@michaelgao88) present 21 ML products translated into clinical care THREADPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
HIMSS, IHE, and HL7 announce global consortium for eHealth Interoperability at
#ONC2020pic.twitter.com/pehNHQ2SP6
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Jakob Steinfeldt proslijedio/la je Tweet
In a opinion essay I wrote with
@zakkohane we ask Epic to stop its aggressive campaign opposing interoperability and to not block patients' rights to computable copies of their health data.https://www.statnews.com/2020/01/27/epic-block-proposed-data-rule/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
We must stop Epic from blocking interoperability of health information - a major key to accelerating future health advances. Great take by
@zakkohane and@mandl of@HarvardDBMI and@Bos_CHIP I hope they lead the charge on this.https://twitter.com/mandl/status/1221770038836899841 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jakob Steinfeldt proslijedio/la je Tweet
After a dismal performance in the
@kaggle RSNA Intracranial Haemorrhage competition I pulled apart the 2nd place solution to see what they had done so right. Post 3 of 4 now up with jupyter notebooks :D Blog series: https://ntentional.squarespace.com/technical/2020/1/24/kaggle-rsna-2nd-place-train-img-classifier … Notebooks: https://github.com/morganmcg1/kaggle_rsna_2nd_place_solution …pic.twitter.com/8EJJUAxhVi
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Jakob Steinfeldt proslijedio/la je Tweet
We're excited to announce our work predicting phenotypes from echocardiogram images with deep learning was published today!
@GhorbaniAmirata@abidlabs@bryandhe@jonc101x@HeartBobH@euanashley@james_y_zou https://www.nature.com/articles/s41746-019-0216-8 …pic.twitter.com/Gi6cclcdLF
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Jakob Steinfeldt proslijedio/la je Tweet
These days, researchers are so focused on data that they seem to forget the value and power of logical reasoning in science. This week in journal club, we applied logical reasoning to evaluate the strength of hypothesis. Here is a summary. 1/pic.twitter.com/T8MPZehCgd
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Jakob Steinfeldt proslijedio/la je Tweet
Subset testing of a commercially available melanoma detection
#AI shows that performance in visually distinct, unusual lesions (ie mucosa or nail beds) drops precipitously. I'll always advocate this info should be available prior to sale, but great to see.#hiddenstratificationpic.twitter.com/6KiEDmdgpH
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