David B Pisoni, William G Kronenberger, Adrienne S Roman, Ann E Geers
Measures of digit span and verbal rehearsal speed in deaf children after more than 10 years of cochlear implantation
Ear and hearing
covid19 pandemic triggered global public health crisis affecting hundreds countries increasing number infected cases developing automated covid19 identification tools based ct images effectively assist clinical diagnosis reduce tedious workload image interpretation expand dataset machine learning methods necessary aggregate cases different medical systems learn robust generalizable models paper proposes novel deep learning joint framework effectively handle heterogeneous datasets distribution discrepancies accurate covid19 identification address crosssite domain shift redesigning covidnets network architecture learning strategy independent feature normalization latent space improve prediction accuracy learning efficiency additionally propose using contrastive training objective enhance domain invariance semantic embeddings boost classification performance dataset develop evaluate method two largescale public covid19 diagnosis datasets containing ct images extensive experiments show method consistently improves performance datasets outperforming original covidnet trained dataset 1327 1515 auc respectively also exceeding existing stateoftheart multisite learning methods