Background: Cervical lymph nodes are prone to involved by a number of pathologic processes. They are common sites for lymphoma, metastasis, and reactive enlargement in a number of conditions. Aims of the study:-Clinical evaluation of patients with cervical lymphadenopathy. Differentiation between benign and malignant lymph nodes by means of ultra sounds (US) and Correlate the US findings with cytological and/or histopathological findings of cervical lymph nodes. Subjects, Materials and Methods:-The present study was carried out over a period of 6 months and included 81 patients of different age groups presenting with cervical lymphadenopathy. Each patient was examined clinically, then comprehensive sonographic examination of the neck for

Background: Breast cancer is the most frequent cancerous tumor and major cause of death from cancer between women all over the world.
Objectives: is to assess if ultrasound features of breast cancer can predict its histopathological grade and HER2 status of breast cancer for patients had their diagnosis in Oncology Teaching Hospital in Medical city complex from September 2014 to November 2015
Patients and Methods: This is retrospective study of 102 patients whom histopathologically proved breast cancer had reviewed their ultrasound findings and correlate them with histopathological grade and HER2 status.
Results: well circumscribed lesions, poorly defined and spiculated lesions are more likely to be of intermediate to high grade

Background: Mammary duct ectasia is defined as dilated duct larger than 2 mm in diameter seen in fibrocystic changes, ductal epithelial hyperplasia, papiloma, DCIS. US has a significant role in diagnostic breast imaging. It is most commonly used as an adjunctive test in characterizing lesions detected by other imaging modalities or by clinical examination

Objective: This study was designed to investigate differences in ultrasonographic findings between malignant and benign mammary duct ectasia.

Patients and Methods: From November 2010 to July 2011, 100 womem with mammary duct ectasia lesions depicted on sonograms were included in this study. We evaluated the ultrasonograp

Background: Mitral valve stenosis is a condition in which the hearts mitral valve is narrowed (stenosis), This narrowing blocks the valve from opening properly obstructing blood flow through the heart and the rest of the body and this causes changes in physical parameters (resistance and conductance). Aim of the study: To assess the changes in the physical parameters in mitral valve stenosis disease in different gender and age by using Doppler ultrasound. Methods : The examination of patients at the Division of Echo - at the Iraqi Center for Heart Disease in Medical City for surgery specialist - Baghdad - Iraq, during(February2009 till November2010). The current study included fifty eight cases containing (27 males and 31 females) ages rang

This work investigates the impacts of eccentric-inclined load on ring footing performance resting on treated and untreated weak sandy soil, and due to the reduction in the footing carrying capacity due to the combinations of eccentrically-inclined load, the geogrid was used as reinforcement material. Ring radius ratio and reinforcement depth ratio parameters were investigated. Test outcomes showed that the carrying capacity of the footing decreases with the increment in the eccentric-inclined load and footing radius ratio. Furthermore, footing tilt and horizontal displacement increase with increasing the eccentricity and inclination angle, respectively. At the same time, the increment in the horizontal displacement due t

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470