F. M. Javed Mehedi Shamrat
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View article: MammoSegNet: a convolutional network analysis for segmenting tumor tissue masses in digital mammograms of breast cancer patients
MammoSegNet: a convolutional network analysis for segmenting tumor tissue masses in digital mammograms of breast cancer patients Open
Breast cancer is one of the leading causes of cancer-related morbidity worldwide, underscoring the need for advanced diagnostic tools to improve early detection and treatment outcomes. This study introduces MammoSegNet, a novel convolution…
View article: Modeling Spatial-Temporal Social Interactions for Pedestrians Trajectory Prediction on Real and Synthetic Datasets
Modeling Spatial-Temporal Social Interactions for Pedestrians Trajectory Prediction on Real and Synthetic Datasets Open
Humans moving in crowded spaces adapt their pace or alter their initial path. A variety of sociocultural factors and personal preferences influence these interactions. With the development of autonomous moving platforms that need to share …
View article: An explainable multi-objective hybrid machine learning model for reducing heart failure mortality
An explainable multi-objective hybrid machine learning model for reducing heart failure mortality Open
As the world grapples with pandemics and increasing stress levels among individuals, heart failure (HF) has emerged as a prominent cause of mortality on a global scale. The most effective approach to improving the chances of individuals’ s…
View article: DPA-HairNet: A Dual Encoder Attention Based Network for Hair Artifact Removal in Dermoscopic Images
DPA-HairNet: A Dual Encoder Attention Based Network for Hair Artifact Removal in Dermoscopic Images Open
Hair artifacts in dermoscopic images significantly hinder the accurate diagnosis of melanoma and other skin conditions by obscuring critical lesion details. To address this challenge, we introduce DPA-HairNet, a novel Dual Encoder Attentio…
View article: Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review
Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review Open
The global spread of SARS-CoV-2 has prompted a crucial need for accurate medical diagnosis, particularly in the respiratory system. Current diagnostic methods heavily rely on imaging techniques like CT scans and X-rays, but identifying SAR…
View article: Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques
Advancing thyroid care: An accurate trustworthy diagnostics system with interpretable AI and hybrid machine learning techniques Open
The worldwide prevalence of thyroid disease is on the rise, representing a chronic condition that significantly impacts global mortality rates. Machine learning (ML) approaches have demonstrated potential superiority in mitigating the occu…
View article: FruitSeg30_Segmentation dataset & mask annotations: A novel dataset for diverse fruit segmentation and classification
FruitSeg30_Segmentation dataset & mask annotations: A novel dataset for diverse fruit segmentation and classification Open
View article: Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis
Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis Open
Gastrointestinal (GI) diseases are prevalent medical conditions that require accurate and timely diagnosis for effective treatment. To address this, we developed the Multi-Fusion Convolutional Neural Network (MF-CNN), a deep learning frame…
View article: An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection
An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection Open
Diabetic retinopathy (DR) involves retina damage due to diabetes, often leading to blindness. It is diagnosed via color fundus injections, but the manual analysis is cumbersome and error-prone. While computer vision techniques can predict …
View article: A Dynamic Selection Hybrid Model for Advancing Thyroid Care With BOO-ST Balancing Method
A Dynamic Selection Hybrid Model for Advancing Thyroid Care With BOO-ST Balancing Method Open
Recently, thyroid disease has been a leading cause of mortality, underscoring the importance of early diagnosis to mitigate its impact. Researchers have randomly employed static selection ensemble methods aiming to forecast the disease in …
View article: BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients
BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients Open
View article: A novel automated feature selection based approach to recognize cauliflower disease
A novel automated feature selection based approach to recognize cauliflower disease Open
Cauliflower disease is a primary cause of reduced cauliflower yield. Preventing cauliflower disease requires early diagnosis. In the scope of this study, we suggested an agro-medical expert system that would make it easier to diagnose caul…
View article: Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset
Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset Open
According to the American cancer society, breast cancer is one of the leading causes of women's mortality worldwide. Early identification and treatment are the most effective approaches to halt the spread of this cancer. The objective of t…
View article: Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset
Breast cancer detection: an effective comparison of different machine learning algorithms on the Wisconsin dataset Open
According to the American cancer society, breast cancer is one of the leading causes of women's mortality worldwide. Early identification and treatment are the most effective approaches to halt the spread of this cancer. The objective of t…
View article: High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images
High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images Open
In this study, multiple lung diseases are diagnosed with the help of the Neural Network algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia, Pneumothorax, Atelectasis, Edema, Effusion, Hernia, Cardiomegaly…
View article: AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images
AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images Open
Alzheimer’s disease is largely the underlying cause of dementia due to its progressive neurodegenerative nature among the elderly. The disease can be divided into five stages: Subjective Memory Concern (SMC), Mild Cognitive Impairment (MCI…
View article: A Novel Fusion Deep Learning Approach for Retinal Disease Diagnosis Enhanced by Web Application Predictive Tool
A Novel Fusion Deep Learning Approach for Retinal Disease Diagnosis Enhanced by Web Application Predictive Tool Open
Retinal disorders such as age-related macular degeneration and diabetic macular edema can lead to permanent blindness. Optical coherence tomography (OCT) enables professionals to observe cross-sections of the retina, which aids in diagnosi…
View article: MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data
MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data Open
Searching, retrieving, and arranging text in ever-larger document collections necessitate more efficient information processing algorithms. Document categorization is a crucial component of various information processing systems for superv…
View article: Blockchain Integrated Neural Networks: A New Frontier in MRI-based Brain Tumor Detection
Blockchain Integrated Neural Networks: A New Frontier in MRI-based Brain Tumor Detection Open
Brain tumors originating from uncontrolled growth of abnormal cells in the brain, presents a significant challenge in healthcare due to their various symptoms and infrequency. While Magnetic Resonance Imaging (MRI) is essential for accurat…
View article: Early Prediction of Chronic Kidney Disease: A Comprehensive Performance Analysis of Deep Learning Models
Early Prediction of Chronic Kidney Disease: A Comprehensive Performance Analysis of Deep Learning Models Open
Chronic kidney disease (CKD) is one of the most life-threatening disorders. To improve survivability, early discovery and good management are encouraged. In this paper, CKD was diagnosed using multiple optimized neural networks against tra…
View article: A predictive analysis framework of heart disease using machine learning approaches
A predictive analysis framework of heart disease using machine learning approaches Open
Heart diseaseis among the leading causes for death globally. Thus, early identification and treatment are indispensable to prevent the disease. In this work, we propose a framework based on machine learning algorithms to tackle such proble…
View article: SkinNet-16: A deep learning approach to identify benign and malignant skin lesions
SkinNet-16: A deep learning approach to identify benign and malignant skin lesions Open
Skin cancer these days have become quite a common occurrence especially in certain geographic areas such as Oceania. Early detection of such cancer with high accuracy is of utmost importance, and studies have shown that deep learning- base…
View article: Internet of things based electrocardiogram monitoring system using machine learning algorithm
Internet of things based electrocardiogram monitoring system using machine learning algorithm Open
In Bangladesh’s rural regions, almost 30% of the population lives in poverty. Rural residents also have restricted access to nursing and diagnostic services due to obsolete healthcare infrastructure. Consequently, as cardiac failure …
View article: LungNet22: A Fine-Tuned Model for Multiclass Classification and Prediction of Lung Disease Using X-ray Images
LungNet22: A Fine-Tuned Model for Multiclass Classification and Prediction of Lung Disease Using X-ray Images Open
In recent years, lung disease has increased manyfold, causing millions of casualties annually. To combat the crisis, an efficient, reliable, and affordable lung disease diagnosis technique has become indispensable. In this study, a multicl…
View article: Analysing most efficient deep learning model to detect COVID-19 from computer tomography images
Analysing most efficient deep learning model to detect COVID-19 from computer tomography images Open
COVID-19 illness has a detrimental impact on the respiratory system, and the severity of the infection may be determined utilizing a selected imaging technique. Chest computer tomography (CT) imaging is a reliable diagnostic techniqu…
View article: Bearing Fault Detection based on Internet of Things using Convolutional Neural Network
Bearing Fault Detection based on Internet of Things using Convolutional Neural Network Open
In the age of the industrial revolution, industry and machinery are elements of the utmost importance to the development of human civilization. As industries are dependent on their machines, regular maintenance of these machines is require…
View article: Supervised machine learning based liver disease prediction approach with LASSO feature selection
Supervised machine learning based liver disease prediction approach with LASSO feature selection Open
In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of t…
View article: COVID-19 Detection Using Deep Learning Algorithm on Chest X-ray Images
COVID-19 Detection Using Deep Learning Algorithm on Chest X-ray Images Open
COVID-19, regarded as the deadliest virus of the 21st century, has claimed the lives of millions of people around the globe in less than two years. Since the virus initially affects the lungs of patients, X-ray imaging of the chest is help…
View article: Sentiment analysis on twitter tweets about COVID-19 vaccines usi ng NLP and supervised KNN classification algorithm
Sentiment analysis on twitter tweets about COVID-19 vaccines usi ng NLP and supervised KNN classification algorithm Open
The pandemic has taken the world by storm. Almost the entire world went into lockdown to save the people from the deadly COVID-19. Scientists around the around have come up with several vaccines for the virus. Amongthem, Pfizer, Moderna, a…
View article: Bangla numerical sign language recognition using convolutional neural networks (CNNs)
Bangla numerical sign language recognition using convolutional neural networks (CNNs) Open
The amount of deaf and mute individuals on the earth is rising at an alarmingrate. Bangladesh has about 2.6 million people who are unable to interact with the community using language. Hearing-impaired citizens in Bangladesh use Bangladesh…