Gudeta Haile Areri, Kiber Temesgen Anteneh, Eden Bishaw Taye, Zelalem Jabessa Wayessa
Breast feeding techniques and associated factors among lactating primipara mothers during the postpartum period in Debre Markos health institutions, North West Ethiopia
Journal of pediatric nursing
deep learning powerful tool became practical 2008 harnessing power graphic processing unites developed rapidly image video natural language processing ongoing developments application deep learning medical data variety tasks across multiple imaging modalities reliability repeatability deep learning techniques utmost importance deep learning considered tool assisting experts including physicians radiologists sonographers owing high costs labeling data deep learning models often evaluated one expert unknown errors fall within clinically acceptable range ultrasound commonly used imaging modality breast cancer screening processes visually estimating risk using breast imaging reporting data system score process highly dependent skills experience sonographers radiologists thereby leading interobserver variability interpretation reasons propose interobserver reliability study comparing performance current topperforming deep learning segmentation model three experts manually segmented suspicious breast lesions clinical ultrasound us images pretrained model using us thyroid segmentation dataset 455 patients 50993 images trained model using us breast segmentation dataset 733 patients 29884 images found mean fleiss kappa value 078 performance three experts breast mass segmentation compared mean fleiss kappa value 079 performance experts optimized deep learning model