Astewil Moges Bazezew, Nurhusen Nuru, Tizta Gebeyehu Demssie, Desalegn Getachew Ayele
Knowledge, practice, and associated factors of preoperative patient teaching among surgical unit nurses, at Northwest Amhara Comprehensive Specialized Referral Hospitals, Northwest Ethiopia, 2022
BMC nursing
one common diseases affecting society around world kidney tumor risk kidney disease increases due reasons consumption readymade food bad habits early diagnosis kidney tumors essential effective treatment reducing side effects reducing number deaths development computeraided diagnostic methods need accurate renal tumor classification also increasing traditional methods based manual detection timeconsuming boring costly highaccuracy tests performed faster lower cost deep learning dl methods kidney tumor detection ktd among current challenges regarding artificial intelligenceassisted ktd obtaining precise programming information capacity group high accuracy make clinical determination vital bring important point current treatment ktd prediction encourages us propose effective dl model effectively assist specialist physicians diagnosis kidney tumors way workload radiologists alleviated errors clinical diagnoses may occur due complex structure kidney prevented large amount data needed training developed methods although various studies conducted reduce amount data feature selection techniques techniques provide little improvement classification accuracy rate paper masked autoencoder mae proposed ktd produce effective results datasets containing samples directly finetuned pretrained selfsupervised learning ssl achieved selfdistillation sd reintroduced configuration loss calculation using masked patches sd loss decoder encoder outputs latent representation calculated operating sslsdktd encoder obtains local attention decoder transfers global attention calculate losses sslsdktd method reached 9804 classification accuracy kauhkidney dataset including 8400 samples 8214 ctkidney dataset containing 840 samples adding external information sslsdktd method transfer learning accuracy results 9982 9524 obtained datasets experimental results shown sslsdktd method effectively extract kidney tumor features limited data aid even alternative radiologists decisionmaking diagnosis disease