Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.
Abstract-One of the most common cause of emergency surgery of the abdomen is acute appendicitis. Early and accurate diagnosis of appendicitis can decrease the morbidity and hospital cost by reducing the delay in diagnosis of appendicitis and its associated complications. In current clinical practice, the measurement of the outer appendiceal diameter by sonographers has been used as one of the indication to confirm acute appendicitis, where the value greater than 6 mm is considered to be a sign of acute appendicitis. However, since ultrasound image itself is in low quality due to speckle noise, error in manual measurement by the sonographers might occur due to wrong detection of the appendiceal edge or wrong placement of the calliper. Thus, we propose certain image processing techniques to enhance the image quality to help sonographers in performing a better diagnosis. This paper proposed a series of image processing method including image enhancement, image segmentation and edge detection before measuring the appendiceal. Selection of image enhancement method is made based on MSE and PSNR values while selection of image segmentation method is made based on the segmented image and execution time. Ten trials of measurement by sonographers using ultrasound and measurement after image processing were gathered. Statistical analyses of both measurements were computed. Mean and standard deviation for the sonographers measurements and measurements after image processing are 4.937±0.14mm and 4.613710±0.08mm respectively. Sonographers measurement showed higher variability compared to measurement after image processing thus measuring the appendiceal diameter after image processing can be helpful for a better diagnosis.
A B S T R A C TPelviureteric junction (PUJ) obstruction is a condition frequently encountered in both adult and pediatric patients. Congenital abnormalities and crossing lower-pole renal vessels are the most common underlying pathologies in both men and women. There are different methods for detecting it the most usual, safe, and easy one is by ultrasound scanning. The aim of this study is how to improve the image quality of two dimensional (2D) ultrasound screening of detecting PUJ dilatation using image processing software, image enhancement, and different types of filters, then making comparison which filter is the best to improve the image quality, that helps the medical doctors, and sonographers to make the correct decision and diagnosis. 1357 patients scanned by ultrasound in Harer general hospital for general abdominal scanning, 987 cases among them have detected as urinary tract infection cases among this 987 case there were 73 case of them with PUJ dilatation. The 2D ultrasound images saved, after making image enhancement and using different types of filters (HE, ADH, CLAHE, and Wiener) to enhance four 2D ultrasound images of abnormal kidneys, the result was in each type of filters there were some advantages and disadvantages, so that the best type of filters are (HE and ADH) because the PUJ and pelvis is much more clear and easy to define after using these kinds of filters.
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