Top Tweets for #SMILEJournalClub

almost 4 years ago

#SMILEJournalClub In this week's journal club, we read paper "RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning", where a radiologic images dataset is created for pertaining models in medical imaging applications.

Joseph Cox @CoxJosephBME

about 4 years ago

Happy to have my first tweet also be my first #SMILEJournalClub, the last of the summer. https://t.co/x9eQvEVsXZ This week's paper is all about the UK Biobank imaging dataset, the worlds largest multi-modal imaging study.

Jordi @jdbardia

over 4 years ago

Pretty cool paper. Coincidentally, it's somewhat relevant to what my group is working on right now. I wonder how the variance between models will be affected when some of the weights are kept the same, and if local recurrent processing would reduce it. #SMILEJournalClub

Kyle See @kylebsee

over 4 years ago

This paper, "Individual differences among deep neural network models", by Mehrer et al. explores how just random network initialization can largely affect individual network differences. https://t.co/1artvxbo0T #SMILEJournalClub

Michael McGaha

@mqmcgaha1

over 4 years ago

Today I read the paper "Individual differences among deep neural network models" which investigates using multiple networks as opposed to a single network and comparing internal representations among networks. https://t.co/0FJ2eIIL5a #SMILEJournalClub

Skylar Stolte @SkylarStolte

over 4 years ago

Mehrer et al. provide important insight into how deep neural networks learn by showing how weight initialization directly affect higher-level data representations. This work supports ensemble learning for complementary information. https://t.co/vYvD6AxyVT #smilejournalclub

Gianna Sweeting @GiannaSweeting

over 4 years ago

#SMILEJournalClub Paper Link: https://t.co/pg7oeKHgnY An interesting read for Journal Club this week. The paper explores the century-old debate of nature vs nurture in terms of AMD cause and progression as well as the use of genetics and imaging data for predicting AMD

YiruMu @mu_yiru

over 4 years ago

This week's journal club is on combining traditional CNN with 52 SNPs and AMD severity to predict late progression of AMD. I wonder why don't they just use fundus images alone, since the model has lower average accuracy when both images and genotype were used? #SMILEJournalClub

Simon Kato @Moncho_K2

over 4 years ago

Fun (?) read about how utilizing genetic information along with colour fundus images can provide an improvement over just colour fundus in the diagnosis of late age-related macular degeneration (AMD). https://t.co/xGFkbmFhI7 #SMILEJournalClub

Top Tweets for #SMILEJournalClub

Last Seen Hashtags on Sotwe

Trends for you

Most Popular Users