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@Radiology_AI 11 months ago
Interested in medical imaging and #MachineLearning? Trainees can apply to join our Trainee Editorial Board https://www.rsna.org/education/trainee-resources/trainee-editorial-boards @judywawira @merelhuisman @KMagudia #journalism #AI #ML https://t.co/9iIzFqAOrf
@Radiology_AI 11 months ago
#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #MSKRad #ML #MachineLearning https://t.co/dQAYmlJEVV
@Radiology_AI 1 year ago
#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #ML #MachineLearning https://t.co/oNMCGLErOr
@Radiology_AI 1 year ago
Spotlight on underreported issues of schema and label noise associated with gold label annotations in medical imaging #AI https://doi.org/10.1148/ryai.220056 @THP_hospital @UofTMedIm @UofT #MachineLearning #ChestRad #ML #ISBI2023 https://t.co/grvq8Z9zWm
@Radiology_AI 1 year ago
Spotlight on underreported issues of schema and label noise associated with gold label annotations in medical imaging #AI https://doi.org/10.1148/ryai.220056 @THP_hospital @UofTMedIm @UofT #MachineLearning #ChestRad #ML https://t.co/gYGKDIjmi5
@Radiology_AI 1 year ago
A #DeepLearning Algorithm for Automatic 3D Segmentation of Rotator Cuff Muscle and Fat from Clinical MRI Scans https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #MSKRad #ML #MachineLearning https://t.co/p2iEGdK9Xo
@Radiology_AI 1 year ago
A #DeepLearning Algorithm for Automatic 3D Segmentation of Rotator Cuff Muscle and Fat from Clinical MRI Scans https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #ML #MachineLearning https://t.co/bTqHsEgj5L
@AliTejaniMD 1 year ago
Highly recommend this opportunity if you are interested in #AI #ML #DataScience and medical journalism! The opportunity to learn from the @Radiology_AI team has been invaluable. #radres More information below ⬇️ https://twitter.com/radiology_ai/status/1643570443574710272
@Radiology_AI 1 year ago
A #DeepLearning Algorithm for Automatic 3D Segmentation of Rotator Cuff Muscle and Fat from Clinical MRI Scans https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #AI #ML #MachineLearning https://t.co/VENfVgFf1M
@Radiology_AI 1 year ago
#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #RotatorCuff #ML #MachineLearning https://t.co/4151Kb3NCk
@Radiology_AI 1 year ago
#DeepLearning algorithm accurately quantifies 3D muscle volume and fat infiltration https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #RotatorCuff #ML #MachineLearning https://t.co/vWxqBTOjel
@Radiology_AI 1 year ago
The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #ML #MachineLearning https://t.co/y3sZ38NIZ7
@Radiology_AI 1 year ago
The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/zkCddWgOZR
@Radiology_AI 1 year ago
A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #Transformers #ML #MachineLearning https://t.co/Yjh54EzRFg
@Radiology_AI 1 year ago
A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/cfC4OrFxC0
@Radiology_AI 1 year ago
A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #ML #MachineLearning https://t.co/d4DFnYAKqL
@Radiology_AI 1 year ago
The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #AI #ML #MachineLearning https://t.co/ij1qLOqOrw
@Radiology_AI 1 year ago
A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #ML #MachineLearning https://t.co/xAASWKqFag
@Radiology_AI 1 year ago
A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/t0Vza8lPaU
@Radiology_AI 1 year ago
Radiologists can offer important contributions to medical student education in #AI https://doi.org/10.1148/ryai.220074 @uazmedphx #MedEd #MachineLearning #ML https://t.co/UbTAada3mc
@Radiology_AI 1 year ago
Point / Counterpoint: Is there room for #AI in medical school? https://doi.org/10.1148/ryai.220074 @uazmedphx #MedEd #MachineLearning #ML https://t.co/3Q34Zg5tXP
@Radiology_AI 1 year ago
#AI models trained on radiology images offer a better starting point for transfer learning in medical imaging https://doi.org/10.1148/ryai.210315 @zahifayad @BMEIIsinai @IcahnMountSinai #DeepLearning #ML #MachineLearning https://t.co/0BxL3KvLfG
@Radiology_AI 1 year ago
"The aim of this article is to discuss data, data creation, and the potential financial stakeholders for the development of #AI in medicine" https://doi.org/10.1148/ryai.220054 @MayoFL_RadRes @ronnie_sebro @MayoRadiology #DataOwnership #ML #MachineLearning https://t.co/2DPMVyczPX
@Radiology_AI 1 year ago
Who Will Get Paid for Artificial Intelligence in Medicine? https://doi.org/10.1148/ryai.220054 @ronnie_sebro @MayoClinic #AI #ML #MachineLearning https://t.co/G33pGSZkXk
@Radiology_AI 1 year ago
Who are the potential financial stakeholders for the development of #AI in medicine? https://doi.org/10.1148/ryai.220054 @ronnie_sebro @MayoClinic #ML #MachineLearning https://t.co/3ftZwhQCU5
@Radiology_AI 1 year ago
Interested in medical imaging and #MachineLearning? Trainees can apply to join our Trainee Editorial Board https://pubs.rsna.org/page/ai/blog/2022/04/ryai_editorsblog0404 @cekahn @judywawira #HITrad #AI #ML https://t.co/u2k19tMSWD
@Radiology_AI 2 years ago
GANs hold promise to facilitate #DeepLearning for personalized and precision medicine https://doi.org/10.1148/ryai.2021200157 @yonsei_u #MSKRad #ML #MachineLearning https://t.co/bncAcFbJD3
@Radiology_AI 3 years ago
Learn how to use #AI techniques to reduce noise in medical images https://doi.org/10.1148/ryai.2020200036 @MayoRadiology @Slowvak #RadAI #ML #MachineLearning https://t.co/20BkcM3V4i
@Radiology_AI 3 years ago
Check out the blog post: "Combatting #Bias in Medical #AI Systems" https://pubs.rsna.org/page/ai/blog/2020/7/ryai_editorsblog0715 @cekahn @PennRadiology #RadAI #ML #MachineLearning https://t.co/htL02Kupck
@Radiology_AI 3 years ago
Check out the blog post: "Combatting #Bias in Medical #AI Systems" https://pubs.rsna.org/page/ai/blog/2020/7/ryai_editorsblog0715 @cekahn @PennRadiology #RadAI #ML #MachineLearning https://t.co/4nh0CNFOj8
@Radiology_AI 3 years ago
Check out the blog post: "Combatting #Bias in Medical #AI Systems" https://pubs.rsna.org/page/ai/blog/2020/7/ryai_editorsblog0715 @cekahn @PennRadiology #RadAI #ML #MachineLearning https://t.co/IJbn1Lq6WC
@Radiology_AI 3 years ago
Failure to consider human factors in past technologies led to poor usability and serious unintended errors https://doi.org/10.1148/ryai.2020190095 @RajRatwani @MedicalHFE #ux #ML #MachineLearning https://t.co/X5D72Rky4N
@Radiology_AI 3 years ago
Development & design of radiology #AI solutions should be done in collaboration with intended users for maximal usability. https://doi.org/10.1148/ryai.2020190095 @RajRatwani @MedicalHFE #RadAI #ML #MachineLearning https://t.co/93osgSbhdB