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Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze medical images with favorable results. It can help save lives faster and rectify some medical errors. In this study, we look at the most up-to-date methodologies for medical image analytics that use convolutional neural networks on MRI images. There are several approaches to diagnosing and classifying brain cancers. Inside the brain, irregular cells grow so that a brain tumor appears. The size of the tumor and the part of the brain affected impact the symptoms.

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the Current Financial Crisis : Causes and Solutions (Iraqi crisis a model , based on the public budget for the fiscal year 2016)
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The research aims to analysis of the current financial crisis in Iraq through knowing its causes and then propose some solutions that help in remedy the crisis and that on the level of expenditures and revenues, and has been relying on the Federal general budget law of the Republic of Iraq for the fiscal year 2016 to obtain the necessary data in respect of the current expenditures and revenues which necessary to achieve the objective of the research , and through the research results has been reached to a set of conclusions which the most important of them that causes of the current financial crisis in Iraq , mainly belonging to increased expenditures and especially the current ones and the lack of revenues , especially non-oil o

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Publication Date
Sat Nov 10 2018
Journal Name
Oriental Journal Of Chemistry
New Series of Substituted Heterocyclics Derived from α , β – Unsaturated Ketone and Their Cytotoxic Activity Tumor Cell Lines
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The aldol condensation of 2-acetylnaphthalene with 9-anthracene carboxaldehyde afforded α, β-unsaturated keton (1) . New heterocyclic compounds containing: cyclohexenone[2], indazole[3], pyrimidinethion [4], thiazolo fused pyrimidine[5], isoxazoline[6], substituted pyrazoline[7]a-d and pyrimidinone[8] rings system were synthesized from α, β-unsaturated keton[1]. Cyclization of [1] with ethylacetoacetate gave the mentioned heterocycle cyclohexanone [2]. The cyclo condensation of [2] with hydrazine gave the new indazole derivative [3]. furthermore, the reation of [1]with thiourea gives thiopyrmidine derivative [4]. The cyclo condensation of [4] with chloroacetic acid gave the fused rings [5]. Then reacted compound[1] with hydroxy

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Publication Date
Sat Sep 01 2018
Journal Name
J Of Baghdad College Of Dentistry
Serum Tumor Necrosis Factor Alpha and High Sensitive C-Reactiveprotein as Biomarkersin Periodontitis in Iraqi Patients with Osteoarthritis
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Publication Date
Fri Feb 01 2013
Journal Name
Ijbpas
THE POSSIBLE RELATIONSHIP BETWEEN SERUM TUMOR NECROSIS FACTOR ALPHA LEVEL AND THE RECOVERY OF PATIENTS WITH PULMONARY TUBERCULOSIS
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Mycobacterium tuberculosis is the cause of the major world health issue, tuberculosis (TB). The cytokine, tumor necrosis factor alpha (TNF-α) has been implicated in protection against TB in the early stages of the disease. TNF-α is an effective cytokine in the killing of intracellular M. tuberculosis. This study inducted to investigate whether there is any relationship between levels of TNF-α in sera of TB patients and their recovery, and is there any difference in the level of this cytokine in sera of female and male TB patients. This study included 29 patients with pulmonary TB (18 female and 11 male), their ages ranging from 37 to 59 years. All of them received first line TB therapy. They were consulted at Pasture Center during Septem

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Publication Date
Fri Nov 01 2019
Journal Name
2019 1st International Informatics And Software Engineering Conference (ubmyk)
Radial Basis Function (RBF) Based on Multistage Autoencoders for Intrusion Detection system (IDS)
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

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Publication Date
Sat Jun 01 2024
Journal Name
Al-rafidain Journal Of Computer Sciences And Mathematics
Braille Character Recognition System: Review
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The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition S

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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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