45 results for "Azhar Imran"
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Journal Article
Fundus imaging based quantum computing: Grading of severity of vision threatening diabetic retinopathy
Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accurate and automated diagnostic systems. This study proposes…
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AI-driven educational transformation in ICT: Improving adaptability, sentiment, and academic performance with advanced machine learning
This study significantly contributes to the sphere of educational technology by deploying state-of-the-art machine learning and deep learning strategies for meaningful changes in education. The hybrid stacking approach did an excellent implementation using Decision Trees, Random Forest, and XGBoost…
Also available at: DOAJ
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A Blockchain Ethereum Technology-Enabled Digital Content: Development of Trading and Sharing Economy Data
The idea of a shared economy becomes one of the companies as an enterprise type. Especially with the advanced development of digital smart devices and the internet, several forms of the mutual economy have been advanced in accord with the need for sharing of separate income. Shareable commodity and…
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Denial of Service (DoS) Defences against Adversarial Attacks in IoT Smart Home Networks using Machine Learning Methods
The availability of information and its integrity and confidentiality are important factors in information and communication of the system security. The DDoS attack generally means Distributed denial of services generates many enormous packets to slow and down the Services for actual users who use…
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Deep-Fed: A comprehensive solution for precise bone fracture identification in athletes
Bone fracture diagnosis is a critical aspect of sports medicine, where accurate and timely detection enables effective treatment and rapid recovery. This study proposes Deep-Fed, a federated deep learning framework for fracture diagnosis in athletes. Deep-Fed integrates convolutional neural…
Also available at: DOAJ
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Journal Article Full text
Adaptive geometric-attention network for two-stage lung nodule segmentation and malignancy classification in federated healthcare IoT edge environments
Accurate segmentation and classification of lung nodules in computed tomography (CT) scans remains a critical challenge in early lung cancer detection within distributed healthcare Internet of Things (IoT) environments. This paper presents a novel two-stage framework called Adaptive…
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A novel fusion of genetic grey wolf optimization and kernel extreme learning machines for precise diabetic eye disease classification
In response to the growing number of diabetes cases worldwide, Our study addresses the escalating issue of diabetic eye disease (DED), a significant contributor to vision loss globally, through a pioneering approach. We propose a novel integration of a Genetic Grey Wolf Optimization (G-GWO)…
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Improved Support Vector Machine based on CNN-SVD for vision-threatening diabetic retinopathy detection and classification
The integration of artificial intelligence (AI) in diagnosing diabetic retinopathy, a major contributor to global vision impairment, is becoming increasingly pronounced. Notably, the detection of vision-threatening diabetic retinopathy (VTDR) has been significantly fortified through automated…
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Comparative Analysis of Vessel Segmentation Techniques in Retinal Images
The blood vessels are the primary anatomical structure that can be visible in retinal images. The segmentation of retinal blood vessels has been accepted worldwide for the diagnosis of both cardiovascular (CVD) and retinal diseases. Thus, it requires an appropriate vessel segmentation method for…
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ResSGA-Net: A deep learning approach for enhanced brain tumor detection and accurate classification in healthcare imaging systems
Accurate and reliable brain tumor classification from magnetic resonance imaging (MRI) is a critical component of computer-aided diagnosis systems, directly impacting clinical decision-making and patient outcomes. This study presents ResSGA-Net, a hybrid deep learning framework that integrates a…
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In-Silico Analysis of Phytocompounds of Olea europaea as Potential Anti-Cancer Agents to Target PKM2 Protein
Globally, cancer is the second leading cause of mortality and morbidity. The growth and development of cancer are extremely complex. It is caused by a variety of pathways and involves various types of enzymes. Pyruvate kinase M2 (PKM2) is an isoform of pyruvate kinase, that catalyses the last steps…
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A survey on VV&A of large-scale simulations
Purpose – Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions…
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Skin Cancer Detection Using Combined Decision of Deep Learners
Cancer is a deadly disease that arises due to the growth of uncontrollable body cells. Every year, a large number of people succumb to cancer and it’s been labeled as the most serious public health snag. Cancer can develop in any part of the human anatomy, which may consist of trillions of…
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ODGNet: a deep learning model for automated optic disc localization and glaucoma classification using fundus images
Abstract Glaucoma is one of the prevalent causes of blindness in the modern world. It is a salient chronic eye disease that leads to irreversible vision loss. The impediments of glaucoma can be restricted if it is identified at primary stages. In this paper, a novel two-phase Optic Disk…
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Implementation and Use of Disease Diagnosis Systems for Electronic Medical Records Based on Machine Learning: A Complete Review
Electronic health records are used to extract patient's information instantly and remotely, which can help to keep track of patients' due dates for checkups, immunizations, and to monitor health performance. The Health Insurance Portability and Accountability Act (HIPAA) in the USA protects the…
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Computer-Aided Early Melanoma Brain-Tumor Detection Using Deep-Learning Approach
Brain tumors affect the normal functioning of the brain and if not treated in time these cancerous cells may affect the other tissues, blood vessels, and nerves surrounding these cells. Today, a large population worldwide is affected by the precarious disease of the brain tumor. Healthy tissues of…
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A Brief Survey on Breast Cancer Diagnostic With Deep Learning Schemes Using Multi-Image Modalities
Patients with breast cancer are prone to serious health-related complications with higher mortality. The primary reason might be a misinterpretation of radiologists in recognizing suspicious lesions due to technical issues in imaging qualities and heterogeneous breast densities which increases the…
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Wearable Regionally Trained AI-Enabled Bruxism-Detection System
Sleep Bruxism (SB) and Awake Bruxism (AB) can cause severe discomfort, exhaustion, and problems with day-to-day functioning, including poor sleep and bad performance at work. This emphasizes the significance of early identification and treatment of bruxism. To date, some tools like mouthpieces have…