Winta Tesfaye, Bezawit Ashine, Yadelew Yimer, Yibeltal Yismaw, Gedamnesh Bitew, Tseganesh Asefa, Kirubel Girmay, Habtu Kifle Negash, Yitbarek Fantahun Marye, Hiwot Tezera
Utilization of cervical cancer screening and determinant factors among female nurses in selected public hospitals in Addis Ababa, Ethiopia
Cancer treatment and research communications
deep learning dl requires large amount training data improve performance prevent overfitting overcome difficulties need increase size training dataset done augmentation small dataset augmentation approaches must enhance models performance learning period several types transformations applied medical images transformations applied entire dataset subset data depending desired outcome study categorize data augmentation methods four groups absent augmentation modifications made basic augmentation includes brightness contrast adjustments intermediate augmentation encompassing wider array transformations like rotation flipping shifting addition brightness contrast adjustments advanced augmentation transformation layers employed plan conduct comprehensive analysis determine group performs best applied brain ct images evaluation aims identify augmentation group produces favorable results terms improving model accuracy minimizing diagnostic errors ensuring robustness model context brain ct image analysis