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Detection and Classification of The Osteoarthritis in Knee Joint Using Transfer Learning with Convolutional Neural Networks (CNNs)
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    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA using transfer learning with fine-tuning. This paper proposed three versions of pre-trained networks (VGG16, VGG19, and ResNet50) for handling the classification task. According to the classification results, The proposed model ResNet50 outperformed the other models a validation accuracy of 91.51% has been obtained.

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Medical Image Classification for Coronavirus Disease (COVID-19) Using Convolutional Neural Networks
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     The coronavirus is a family of viruses that cause different dangerous diseases that lead to death. Two types of this virus have been previously found: SARS-CoV, which causes a severe respiratory syndrome, and MERS-CoV, which causes a respiratory syndrome in the Middle East. The latest coronavirus, originated in the Chinese city of Wuhan, is known as the COVID-19 pandemic. It is a new kind of coronavirus that can harm people and was first discovered in Dec. 2019. According to the statistics of the World Health Organization (WHO), the number of people infected with this serious disease has reached more than seven million people from all over the world. In Iraq, the number of people infected has reached more than tw

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Publication Date
Thu Sep 12 2019
Journal Name
Al-kindy College Medical Journal
Association of radiological osteoarthritis of the knee joint with locomotor disability
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Background:  Knee osteoarthritis (KOA) is a common joint disorder leading to considerable pain and locomotor disability in lower limb function. Locomotor disability, which is difficulty in activities of daily living related to lower limb function, can be the consequence of KOA, so early diagnosis and management may improve quality of life.

Objective: To assess the contribution of radiological osteoarthritis of the knees to disability in the activities of daily living related to lower limb function.

 Methods: One hundred twenty Iraqi KOA patients (104 females and 16 males) who were attending to Rheumatology Unit, Full history was taken and complete clinical exami

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Detection of COVID-19 in X-Rays by Convolutional Neural Networks
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      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Electrical stimulation for the treatment of Knee joint osteoarthritis
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Abstract 20 patients with osteoarthritis of the knee joint were treated by electrical stimulation in the form of 6 sessions every other day each sessions of diphase fixe (DF) for 4 minutes followed by rest for 4 minutes then treated with a monophase fixe (MF) for 2 minutes. By clinical & statistical analysis ( P value < 0.05) we conclude that the electrical stimulation is effective as one method in the treatment of osteoarthritis.

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Publication Date
Wed Oct 31 2018
Journal Name
Al-kindy College Medical Journal
Efficacy Of Hyaluronic Acid And Corticosteroid Intra-Articular Injection In Knee Joint With Primary Osteoarthritis
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Background: Osteoarthritis OA is the most common joint disorder in the world. Injection of high molecular weight hyaluronic acid intra-articular with steroid is a one of the used therapeutic option for patients with (OA)knee.

Objectives: Objective of this study was the evaluation the efficacy, safety, pluse duration of action of viscosupplementation of the  HMWHA( high molecular weight hyluranic acid ).

Type of the study: Cross-sectional study.

Methods: From 81 patients with sever knee pain due to OA (grades 3–4) were recruited from Al-Yarmouk teaching hospital  & a private clinic during the period from January 2014 till July 2016.

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Mon Mar 27 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of the Clinical use of Metformin or Pioglitazone in Combination with Meloxicam in Patients with Knee Osteoarthritis; using Knee Injury and Osteoarthritis outcome Score
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Osteoarthritis is the most prevalent arthritic disease and a leading cause of disability. The pathogenesis of osteoarthritis involves multiple etiologies, including variable degree of synovial inflammation. Metformin and pioglitazone could potentially reduce the levels and activity of inflammatory mediators. This may consider as a new therapeutic approach added to the current used drugs in an attempt to decrease the pain, inflammation, and improve daily activity and quality of life in patients with knee osteoarthritis.

This study designed to evaluate the clinical utility of using metformin or pioglitazone as anti-inflammatory agents in combination with non-steroidal anti-inflammatory drugs (NSAID) of selective type of cyclooxygen

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