Ashenafi Hailu, Birhanu Zeleke, Zeberihe Ermias, Fasil Kenea Duguma, Sara Dula, Samson Wakuma Abaya, Seblework Mekonen Shegen, Gudina Terefe Tucho, Tariku Neme Afata
Prevalence and associated factors of noise-induced hearing loss among workers in Bishoftu Central Air Base of Ethiopia
Scientific reports
deep learning class machine learning methods gaining success attracting interest many domains including computer vision speech recognition natural language processing playing games deep learning methods produce mapping raw inputs desired outputs eg image classes unlike traditional machine learning methods require handengineered feature extraction inputs deep learning methods learn features directly data advent large datasets increased computing power methods produce models exceptional performance models multilayer artificial neural networks loosely inspired biologic neural systems weighted connections nodes neurons network iteratively adjusted based example pairs inputs target outputs backpropagating corrective error signal network computer vision tasks convolutional neural networks cnns proven effective recently several clinical applications cnns proposed studied radiology classification detection segmentation tasks article reviews key concepts deep learning clinical radiologists discusses technical requirements describes emerging applications clinical radiology outlines limitations future directions field radiologists become familiar principles potential applications deep learning medical imaging rsna 2017