AASAH Enass J Waheed, Shatha MH Obaid, Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2019 - Cited by 5

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The study aimed to identify the impact of the use of systemic approach in the collection of geographical material and cognitive motivation when fifth grade students of literary, experimental design researcher adopted a partial seizures, and telemetric to two unequal one experimental and the other officer.
The sample consisted of fifth grade literary students from secondary (inherent) for Boys in Baghdad (the Republic of Iraq. (By Mjootain, and the number of students of each group (30 students). And has rewarded the two groups, in the variables (chronological age, average scores half-year, degree IQ),
Promising researcher himself requirements of research to determine the scientific material and teaching plans and the formulation of

Objective: to evaluate body image and depression symptoms of children with precocious puberty, and find out association between children`s sociodemographic characteristics and their body image and depression signs. Methodology: A cross sectional study, sample of (80) child from both gender, > 7 years were included due to their ability to express their own feeling, diagnosed with precocious puberty, attending out-patient endocrine clinics at pediatric hospitals in Baghdad city. Data collected, during the period from May to November 2018. Consent form has taken from children and their guardians to participate in study. Child body image scale (CBIS) was used to evaluate children body satisfaction (1) and Mood and feeling questionnaire (M