Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

    The plant Borago officinalis, which belongs to the Boraginaceae family and Celebrated as borage, is one of the useful medicinal plants cultivated in Iraq. It was used in olde medicine in Iraq, Irane, Syria and Europe for management of various diseases. It is commonly used as an atonic, tranquilliser, management of cough, sore throat, pneumonia, swelling, inflammatory diseases, antioxidant, and anticancer. This project provides the first comprehensive research done in Iraq to study the phytochemicals and the methods of extraction and isolation of active constituents from Borago officinalis cultivated in Iraq. The plant was harvested in spring from AL-Rifai, Nassiriyah city, IRAQ in February 2019.were w

Pseudomonas aeruginosa is the most common opportunistic pathogen causing morbidity and mortality in hospitalized patients due to its multiple resistance mechanisms. Therefore, as a therapeutic option becomes restricted, the search for a new agent is a preference. So P. aeruginosa is an extremely versatile Gram-negative bacterium capable of thriving in a broad spectrum of environments, and this performs main problems to workers in the field of health. One hundred and fifty samples were collected from different sources from Baghdad hospitals, divided into two main groups: clinical (100) specimens and (50) samples as an environmental, collected from October 2019 to the March 2020. All of these samples were cultured by specific and differential

The presence and prevalence of V. cholerae were investigated in forty five water samples collected from different locations of Tiger River/ Baghdad city. Twenty one isolates were isolated by adopting a simple isolation techniques. The final identification revealed that only three isolates were confirmed as V. cholerae. They were named 1J, 1R and Dial 131 which are all serogrouped as non-O1. Toxin Coregulated Pili (TCP) and heat labile enterotoxin (LT) were determined in only the environmental isolate 1J while non of the isolates produced heat stabile toxin (ST). The purification scheme was improved, few steps were adopted to include back extraction of ammonium sulfate, saturation between 80-20%, desalting through Sephadex G25, and gel filt