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Results for “"Mirjam Jonkman"”

31+ results

A Computer-Aided Diagnostic System to Identify Diabetic Retinopathy, Utilizing a Modified Compact Convolutional Transformer and Low-Resolution Images to Reduce Computation Time

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Inam Ullah Khan, Mohaimenul Azam Khan Raiaan, Kaniz Fatema, Sami Azam et al.

Journal: BiomedicinesYear: 2023Citations: 38

Diabetic retinopathy (DR) is the foremost cause of blindness in people with diabetes worldwide, and early diagnosis is essential for effective treatment. Unfortunately, the present DR screening method requires the skill of ophthalmologists and is time-consuming. In this study, we present an automate...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Use of Efficient Machine Learning Techniques in the Identification of Patients with Heart Diseases

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Pronab Ghosh, Sami Azam, Asif Karim, Mirjam Jonkman et al.

Year: 2021Citations: 37

Cardiovascular disease has become one of the world's major causes of death. Accurate and timely diagnosis is of crucial importance. We constructed an intelligent diagnostic framework for prediction of heart disease, using the Cleveland Heart disease dataset. We have used three machine learning appro...

Health SciencesHealth ProfessionsHealth Information Management
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MNet-10: A robust shallow convolutional neural network model performing ablation study on medical images assessing the effectiveness of applying optimal data augmentation technique

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Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Md. Zahid Hasan et al.

Journal: Frontiers in MedicineYear: 2022Citations: 35

Interpretation of medical images with a computer-aided diagnosis (CAD) system is arduous because of the complex structure of cancerous lesions in different imaging modalities, high degree of resemblance between inter-classes, presence of dissimilar characteristics in intra-classes, scarcity of medic...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity

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Sidratul Montaha, Sami Azam, A. K. M. Rakibul Haque Rafid, Sayma Islam et al.

Journal: PLoS ONEYear: 2022Citations: 34

The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class resemblance between malignant and benign lesions, and the presence of various artifacts including hairs make automated melanoma recognition in dermoscopy images quite challenging. To date, various co...

Health SciencesMedicineOncologyOpen Access
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ECgMLP: A novel gated MLP model for enhanced endometrial cancer diagnosis

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Md. Alif Sheakh, Sami Azam, Mst. Sazia Tahosin, Asif Karim et al.

Journal: Computer Methods and Programs in Biomedicine UpdateYear: 2025Citations: 21

• ECgMLP offers a novel approach for automated diagnosis of endometrial cancer. • Advanced preprocessing boosts histopathological image quality and accuracy. • Otsu thresholding and watershed aid in precise image segmentation. • ECgMLP achieves 99.26 % accuracy, surpassing prior diagnostic technique...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Development of an automated optimal distance feature-based decision system for diagnosing knee osteoarthritis using segmented X-ray images

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Kaniz Fatema, Md. Awlad Hossen Rony, Sami Azam, Md. Saddam Hossain Mukta et al.

Journal: HeliyonYear: 2023Citations: 18

Knee Osteoarthritis (KOA) is a leading cause of disability and physical inactivity. It is a degenerative joint disease that affects the cartilage, cushions the bones, and protects them from rubbing against each other during motion. If not treated early, it may lead to knee replacement. In this regar...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Cervical spine fracture detection utilizing YOLOv8 and deep attention-based vertebrae classification ensuring XAI

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Debopom Sutradhar, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Mirjam Jonkman et al.

Journal: Biomedical Signal Processing and ControlYear: 2024Citations: 17

• Automated detection and classification of cervical spine fractures using CT scans. • Combining YOLOv8 object detection with a novel attention-based CNN (VertNet-10). • Achieved 93 % mAP for fracture detection and 99.55 % accuracy in vertebrae classification. • Class activation maps enhance the mod...

Physical SciencesEngineeringBiomedical EngineeringOpen Access
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Automated Detection of Broncho-Arterial Pairs Using CT Scans Employing Different Approaches to Classify Lung Diseases

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Sami Azam, A. K. M. Rakibul Haque Rafid, Sidratul Montaha, Asif Karim et al.

Journal: BiomedicinesYear: 2023Citations: 17

Current research indicates that for the identification of lung disorders, comprising pneumonia and COVID-19, structural distortions of bronchi and arteries (BA) should be taken into account. CT scans are an effective modality to detect lung anomalies. However, anomalies in bronchi and arteries can b...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Graph neural network-based breast cancer diagnosis using ultrasound images with optimized graph construction integrating the medically significant features

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Sadia Sultana Chowa, Sami Azam, Sidratul Montaha, Israt Jahan Payel et al.

Journal: Journal of Cancer Research and Clinical OncologyYear: 2023Citations: 16

PURPOSE: An automated computerized approach can aid radiologists in the early diagnosis of breast cancer. In this study, a novel method is proposed for classifying breast tumors into benign and malignant, based on the ultrasound images through a Graph Neural Network (GNN) model utilizing clinically ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Using feature maps to unpack the CNN ‘Black box’ theory with two medical datasets of different modality

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Sami Azam, Sidratul Montaha, Kayes Uddin Fahim, A. K. M. Rakibul Haque Rafid et al.

Journal: Intelligent Systems with ApplicationsYear: 2023Citations: 16

Convolutional neural networks (CNNs) have been established for a comprehensive range of computer vision problems across several benchmarks. Visualization and analysis of feature maps generated by convolutional layers can be an effective approach to explore the hidden and complex characteristic of a ...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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An effective approach to address processing time and computational complexity employing modified CCT for lung disease classification

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Inam Ullah Khan, Sami Azam, Sidratul Montaha, Abdullah Al Mahmud et al.

Journal: Intelligent Systems with ApplicationsYear: 2022Citations: 16

Early identification and adequate treatment can help prevent lung disorders from becoming chronic, severe, and life-threatening. X-ray images are commonly used and an automated and effective method involving deep learning techniques can potentially contribute to quick and accurate diagnosis of lung ...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Artificial Intelligence-Driven Advancements in Otitis Media Diagnosis: A Systematic Review

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Md. Awlad Hossen Rony, Kaniz Fatema, Mohaimenul Azam Khan Raiaan, Md. Mehedi Hassan et al.

Journal: IEEE AccessYear: 2024Citations: 15

Otitis Media (OM), predominantly affecting children, is a significant global health issue, with an estimated 360 million pediatric cases yearly worldwide. OM causes mild and moderate conductive hearing loss which can be disabling for young children, particularly during the first three years of life ...

Health SciencesMedicineOtorhinolaryngologyOpen Access
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An Automated Decision Support System to Analyze Malignancy Patterns of Breast Masses Employing Medically Relevant Features of Ultrasound Images

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Sami Azam, Sidratul Montaha, Mohaimenul Azam Khan Raiaan, A. K. M. Rakibul Haque Rafid et al.

Journal: Journal of Imaging Informatics in MedicineYear: 2024Citations: 13

An automated computer-aided approach might aid radiologists in diagnosing breast cancer at a primary stage. This study proposes a novel decision support system to classify breast tumors into benign and malignant based on clinically important features, using ultrasound images. Nine handcrafted featur...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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A novel Data and Model Centric artificial intelligence based approach in developing high-performance Named Entity Recognition for Bengali Language

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Khadija Akter Lima, Khan Md. Hasib, Sami Azam, Asif Karim et al.

Journal: PLoS ONEYear: 2023Citations: 13

Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of domain specific applications in Natural Language Processing (NLP). According to the type of application, the goal of NER is to identify target entities based on the context of other existing entities...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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A Low Complexity Efficient Deep Learning Model for Automated Retinal Disease Diagnosis

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Sadia Sultana Chowa, Md. Rahad Islam Bhuiyan, Israt Jahan Payel, Asif Karim et al.

Journal: Journal of Healthcare Informatics ResearchYear: 2025Citations: 10

The identification and early treatment of retinal disease can help to prevent loss of vision. Early diagnosis allows a greater range of treatment options and results in better outcomes. Optical coherence tomography (OCT) is a technology used by ophthalmologists to detect and diagnose certain eye con...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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