@Radiology_AI 10 months ago
Differences in data distribution may affect federated #DeepLearning model performance in medical image segmentation https://doi.org/10.1148/ryai.220082 @ND_CSE @hku_science @ZJU_China #FederatedLearning #AI #MachineLearning #AIME23 #AIME2023 https://t.co/Sg0Y2jheGy
@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 #DeepLearning #RotatorCuff #MachineLearning https://t.co/zDjQ4xANb8
@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 #BERT #DeepLearning #MachineLearning https://t.co/924nXgpWwb
@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
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
@globaliqx 2 years ago
New #MachineLearning model could speed up the process of developing new medicines https://buff.ly/3Hp2MIy #AI #eHealth #IoT #DigitalTransformation #DeepLearning @JoannMoretti @PawlowskiMario @CurieuxExplorer @MargaretSiegien https://t.co/RiRllSfmzB
@Michael_D_Moor 2 years ago
Preprint alert! Interested in #MachineLearning in #medicine and #sepsis? We developed and validated a #DeepLearning model for predicting sepsis across 5 ICU databases from 3 countries featuring 156k ICU stays and 783 patient years worth of monitoring data. A 🧵. 1/n https://t.co/4RL3UaXYIY
@BigDataQueen_me 3 years ago
Nature article: #DeepLearning model to detect early stage of glaucoma, trained on OCT images #bigDataQueen #Python #MachineLearning #AI #100DaysOfCode #DEVCommunity #IoT #womenintech #womeininStem #RStats #Biomed #ML #DataScience #neuralnetwork #medical https://www.nature.com/articles/s41598-020-76154-7 https://t.co/WObUNhRPvH
@gp_pulipaka 4 years ago
#DeepLearning and Medical Imaging — Interpret What The Model Sees? #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #HealthTech http://bit.ly/2PEZCYe https://t.co/6vSuzvxjnW
@ipfconline1 4 years ago
Explainable #AI for Science and Medicine [Video w/ Scott Lundberg] Understanding why a #machinelearning model makes a certain prediction is crucial https://buff.ly/2Lyufyc @MSFTResearch #AI #DeepLearning #AIEthics #HealthTech Cc @AkwyZ @AlaricAloor @Info_Data_Mgmt @AghiathChbib https://t.co/B30kH7SlYK