Bettina Baeßler
@Baessler_Rad
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UKW #radiologist; #radiomics; #MachineLearning; #deeplearning; #AI; #CMR; education; #diversity; #inclusion; @DRG.de; @EurRadiology
Würzburg, Germany
Joined November 2017
RT @HyunKoMD: Fresh off the press @EurRadiology .Advancing radiomics research translation through a public database..
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Congratulations to the winners! 👏🥳 Well deserved. #EuropeanRadiology @renatocuocolo @cannella_rob @EurRadiology @InsightsImaging @EuSoMII.
link.springer.com
European Radiology - The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically...
@EuSoMII Award to the most cited papers in @InsightsImaging and @EurRadiology! . Congratulations to the winners 🏆 🏆 . @renatocuocolo @pintodrad
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Interesting study on the reproducibility of radiomics 👇 #EuropeanRadiology.
Using a convolutional neural network-based image conversion technique significantly improves the reproducibility of radiomic features in hepatocellular carcinomas. (Heejin Lee et al). #EuropeanRadiology . 🔗
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RT @EurRadiology: This study demonstrates the validity and reliability of automated ASPECTS evaluation for supporting neurologists in the c….
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RT @EurRadiology: The reproducibility across different VOI sizes in normal #liver #MRI was improved when translating images into parametric….
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I really like the new graphical abstracts in @EurRadiology! 👏 What do you think of it?.
📣 Introducing this exciting new meta-research by Dr. Hameed et al (@MairaHameed_) from @UCLHresearch @DoM_UCL published in #EuropeanRadiology. Follow the 🧵 for more insight by Dr. Hameed. 1/6
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RT @EurRadiology: Application of #AI-derived contours yields results comparable to manual segmentations. (Jan Gröschel et al.). #EuropeanRa….
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Interesting study, thanks for sharing @BernhardKainz1 !.
📢 Just out! A leap in object segmentation using pre-trained latent diffusion models! Generate accurate foreground-background models from textual descriptions WITHOUT segmentation labels. 🚀 Surpasses prior methods and nears fully supervised training. 🩺#AIResearch @BorderlessSci
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RT @InsightsImaging: Critical Review: #Radiology #ArtificialIntelligence, a systematic evaluation of methods (RAISE). (@BSKellyRad et al.)….
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RT @InsightsImaging: Educational Review: Role of diagnostic imaging in psoriatic #arthritis - how, when, and why. (Ana María Crespo-Rodrígu….
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Still an underrecognized problem, but a tremendously important one (of course, not only in #radiology)! Interesting read 👇👇 #EuropeanRadiology.
How prevalent is #burnout among #radiology residents and what are the risks? (Ziqi Wan et al.). #EuropeanRadiology. Want to read more? Click the link below ⬇️ .
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RT @EurRadiology: Commentary: Generalizability of prostate #MRI deep learning: does one size fit all data? (@StanzioneMD & @renatocuocolo)….
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RT @EurRadiology: Commentary: Explainable #AI - current status and future potential. (@BasvanderVelden). #EuropeanRadiology. Read the full….
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RT @francisdeng: Apps for radiology residency are due soon. Do you know how competitive it's been?.We reviewed match data: .
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Thanks for sharing @Tugba_Akinci_MD! Looking forward to seeing more studies adhering to checklists like #CLAIM in the future. @EurRadiology.
Using the @Radiology_AI #CLAIM checklist is a crucial component in ensuring high-quality reporting of AI research in radiology. According to the recently published CLAIM citation analysis:.🧵👇
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RT @Klonmich: The reproducibility of RQS is extremely low. This has now been highlighted in @EurRadiology and should be taken into account….
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Congrats on this important work, dear Radiomics Auditing Group! @EuSoMII.
The RQS has undoubtedly had an important role in raising awareness on #radiomics and #MachineLearning research. It's also showing limitations, as seen in the latest @EuSoMII Radiomics Auditing Group paper. Now available on @EurRadiology (#openaccess).
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RT @EurRadiology: #Cardiac implantable electronic device-related artefacts may reduce the diagnostic value of cardiac magnetic resonance. (….
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RT @Dr_ASChaudhari: Thanks @_akhaliq for featuring this work! A full thread on the methods/implications is.
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