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@Radiology_AI 1 year 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 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
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
#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 2 years 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