@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
The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #AI #MachineLearning https://t.co/SlT3r4lHqe
@Radiology_AI 1 year ago
Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #Transformer #DeepLearning #MachineLearning https://t.co/vkN17E7Iso
@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 #DeepLearning #MachineLearning https://t.co/924nXgpWwb
@Radiology_AI 1 year ago
Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #AI #MachineLearning https://t.co/ATFyMZCVZE
@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 #DeepLearning #MachineLearning https://t.co/DVl9XtgTBI
@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
Toward Foundational Deep Learning Models for Medical Imaging in the New Era of Transformer Networks https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #Transformers #Transformer #MachineLearning https://t.co/xKfodRdUM4
@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 #Transformers #AI #MachineLearning https://t.co/68vIIKCDag
@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
The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #DeepLearning #MachineLearning #AMIA2022 https://t.co/LvndChK6Cw
@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
@StanfordMed 2 years ago
"The white body and the male body have long been the norm in #medicine, guiding drug discovery, treatments and standards of care," said Londa Schiebinger, PhD. "It's important that we do not let #AI devices fall into that historical pattern." https://scopeblog.stanford.edu/2021/06/08/to-benefit-diverse-groups-ai-must-address-bias-researchers-say/ #DataScience
@WiDS_Conference 3 years ago
Manisha Desai of @StanfordMed sits at the intersection of #medicine and #datascience. On the #WiDSPodcast she discusses the #COVID19 clinical trials and preventing disease progression: https://bit.ly/manisha-desai @AnitaB_org @GirlsWhoCode @DataWomen @WiMLworkshop @AmstatNews @WITI https://t.co/QeLplvX0nR
@HSLavoie 4 years ago
47% of physicians and 73% of medical students said that they are currently seeking out additional training to prepare for data and #digitalhealth innovations. Top areas were adv. statistics, #datascience + population health management. https://stan.md/2NSQSNv @StanfordMed
@TheFHFoundation 4 years ago
A8 #FINDFH is the FH Foundation’s #precisionmedicine, combining #AI and #bigdata to find individual health records that look like FH and work with healthcare systems to diagnose and treat. @OHSU @PennMedicine @StanfordMed @npj Digital Medicine: https://thefhfoundation.org/findfh-data-published-in-npj #KnowFH https://t.co/Xbsju94trI