Saadullah Farooq Abbasi
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View article: A Novel and Secure 3D Colour Medical Image Encryption Technique Using 3D Hyperchaotic Map, S-box and Discrete Wavelet Transform
A Novel and Secure 3D Colour Medical Image Encryption Technique Using 3D Hyperchaotic Map, S-box and Discrete Wavelet Transform Open
Over the past two decades, there has been a substantial increase in the use of the Internet of Medical Things (IoMT). In the smart healthcare setting, patients’ data can be quickly collected, stored and processed through insecure medium su…
View article: Recent Advances in Generative Models for Synthetic Brain MRI Image Generation
Recent Advances in Generative Models for Synthetic Brain MRI Image Generation Open
With the use of artificial intelligence (AI) for image analysis of Magnetic Resonance Imaging (MRI), the lack of training data has become an issue. Realistic synthetic MRI images can serve as a solution and generative models have been prop…
View article: Analysing the Association Between User Perceptions and Usage Patterns of Digital Personalised Care Platforms Using the UTAUT Framework: Insights from the ADLIFE Project
Analysing the Association Between User Perceptions and Usage Patterns of Digital Personalised Care Platforms Using the UTAUT Framework: Insights from the ADLIFE Project Open
This study explores the relationship between user perceptions, as measured by the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, and actual usage patterns of the ADLIFE Digital Personalized Care Platform. Data w…
View article: Advances in breast cancer diagnosis: a comprehensive review of imaging, biosensors, and emerging wearable technologies
Advances in breast cancer diagnosis: a comprehensive review of imaging, biosensors, and emerging wearable technologies Open
Breast cancer has been the most frequent diagnosed cancer and the leading cause of cancer-related deaths among women worldwide, mainly due to delayed detection. Early diagnosis significantly improves prognosis and long-term survival rates.…
View article: Transforming Healthcare: The Role of Artificial Intelligence
Transforming Healthcare: The Role of Artificial Intelligence Open
The integration of artificial intelligence (AI) into healthcare is revolutionising the industry by enhancing diagnostic accuracy, personalising treatment strategies, and improving administrative efficiency. This study aims to evaluate the …
View article: Preliminary Exploration of Pre-Trained Vision-Language Models for Cyber-Threat Modelling in Internet of Medical Things (IoMT)
Preliminary Exploration of Pre-Trained Vision-Language Models for Cyber-Threat Modelling in Internet of Medical Things (IoMT) Open
The field of image processing is undergoing a significant transformation, driven by the advancements in vision-language models (VLMs) based on groundbreaking transformer architectures. With the expansion of Internet of Medical Things (IoMT…
View article: Patients vs. Healthcare Providers: A Comparative Analysis of Technology Acceptance Using the UTAUT Model
Patients vs. Healthcare Providers: A Comparative Analysis of Technology Acceptance Using the UTAUT Model Open
This study examines the differences in technology acceptance of electronic Patient Empowerment Platforms (PEP) and Personalised Care Plan Management Platforms (PCPMP) between two distinct user groups: patients/caregivers and healthcare pro…
View article: A novel transformer-based approach for cardiovascular disease detection
A novel transformer-based approach for cardiovascular disease detection Open
According to the World Health Organization, cardiovascular diseases (CVDs) account for an estimated 17.9 million deaths annually. CVDs refer to disorders of the heart and blood vessels such as arrhythmia, atrial fibrillation, congestive he…
View article: Understanding User Experiences on Patient Empowerment and Personalised Care Platforms: A Longitudinal Analysis Through the Extended UTAUT Model
Understanding User Experiences on Patient Empowerment and Personalised Care Platforms: A Longitudinal Analysis Through the Extended UTAUT Model Open
This study investigates the factors influencing the adoption and sustained use of the Patient Empowerment Platform (PEP) and Personalised Care Plan Management Platform (PCPMP) among patients and healthcare providers. Using the extended Uni…
View article: Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer
Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer Open
Advances in computer vision have shown interesting results in synthetic image generation. Diffusion models have shown promising outputs while generating realistic images from textual inputs like stable diffusion and Imagen. However, their …
View article: EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification
EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification Open
An optimal arrangement of electrodes during data collection is essential for gaining a deeper understanding of neonatal sleep and assessing cognitive health in order to reduce technical complexity and reduce skin irritation risks. Using el…
View article: 1D-CNN-IDS: 1D CNN-based Intrusion Detection System for IIoT
1D-CNN-IDS: 1D CNN-based Intrusion Detection System for IIoT Open
The demand of the Internet of Things (IoT) has witnessed exponential growth. These progresses are made possible by the technological advancements in artificial intelligence, cloud computing, and edge computing. However, these advancements …
View article: Development of a CNN for Adult Brain Tumour Characterisation: Implications and Future Directions for Transfer Learning
Development of a CNN for Adult Brain Tumour Characterisation: Implications and Future Directions for Transfer Learning Open
Brain tumours are the most commonly occurring solid tumours in children, albeit with lower incidence rates compared to adults. However, their inherent heterogeneity, ethical considerations regarding paediatric patients, and difficulty in l…
View article: Deep Learning-Based Synthetic Skin Lesion Image Classification
Deep Learning-Based Synthetic Skin Lesion Image Classification Open
Advances in general-purpose computers have enabled the generation of high-quality synthetic medical images that human eyes cannot differ between real and AI-generated images. To analyse the efficacy of the generated medical images, this st…
View article: INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support
INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support Open
Digital health solutions hold promise for enhancing healthcare delivery and patient outcomes, primarily driven by advancements such as machine learning, artificial intelligence, and data science, which enable the development of integrated …
View article: A Deep Features-Based Approach Using Modified ResNet50 and Gradient Boosting for Visual Sentiments Classification
A Deep Features-Based Approach Using Modified ResNet50 and Gradient Boosting for Visual Sentiments Classification Open
The versatile nature of Visual Sentiment Analysis (VSA) is one reason for its rising profile. It isn't easy to efficiently manage social media data with visual information since previous research has concentrated on Sentiment Analysis (SA)…
View article: A Single Channel-Based Neonatal Sleep-Wake Classification using Hjorth Parameters and Improved Gradient Boosting
A Single Channel-Based Neonatal Sleep-Wake Classification using Hjorth Parameters and Improved Gradient Boosting Open
Sleep plays a crucial role in neonatal development. Monitoring the sleep patterns in neonates in a Neonatal Intensive Care Unit (NICU) is imperative for understanding the maturation process. While polysomnography (PSG) is considered the be…
View article: An IoT and Machine Learning-based Neonatal Sleep Stage Classification
An IoT and Machine Learning-based Neonatal Sleep Stage Classification Open
Sleep, in neonates, is used to access the quality of brain and physical development. Typically, neonatal sleep has been divided into three stages: active sleep (AS), quiet sleep (QS), and intermediate sleep (IS). Polysomnography (PSG) is c…
View article: Piezoelectric polymer based acoustic energy harvester for implantable medical devices
Piezoelectric polymer based acoustic energy harvester for implantable medical devices Open
Wireless implantable devices (WIDs) have the potential to revolutionize biomedical sensing, but their power supplies face significant challenges. Traditional energy transfer methods such as inductive and RF have limitations due to associat…
View article: Optimizing Tumor Classification Through Transfer Learning and Particle Swarm Optimization-Driven Feature Extraction
Optimizing Tumor Classification Through Transfer Learning and Particle Swarm Optimization-Driven Feature Extraction Open
Brain tumors pose a significant threat, especially when not detected early. The Inception v3 machine learning model has found extensive applications in computer vision and related fields. This study aims to develop a robust transfer learni…
View article: Single-Channel EEG Data Analysis Using a Multi-Branch CNN for Neonatal Sleep Staging
Single-Channel EEG Data Analysis Using a Multi-Branch CNN for Neonatal Sleep Staging Open
Neonatal sleep staging is crucial for understanding infant brain development and assessing neurological health. This study explores the optimal electrode configuration to reduce technical complexities and potential risks of causing skin ir…
View article: A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection
A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection Open
The Industrial Internet of Things (IIoT) comprises a variety of systems, smart devices, and an extensive range of communication protocols. Hence, these systems face susceptibility to privacy and security challenges, making them prime targe…
View article: Automatic neonatal sleep stage classification: A comparative study
Automatic neonatal sleep stage classification: A comparative study Open
View article: A convolutional neural network-based decision support system for neonatal quiet sleep detection
A convolutional neural network-based decision support system for neonatal quiet sleep detection Open
Sleep plays an important role in neonatal brain and physical development, making its detection and characterization important for assessing early-stage development. In this study, we propose an automatic and computationally efficient algor…
View article: Electroencephalography (EEG) Based Neonatal Sleep Staging and Detection Using Various Classification Algorithms
Electroencephalography (EEG) Based Neonatal Sleep Staging and Detection Using Various Classification Algorithms Open
Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system. EEG based neonatal sleep staging provides valuable information about an infant’s growth and health, but is challeng…
View article: Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques
Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques Open
Breast cancer is one of the leading causes of increasing deaths in women worldwide. The complex nature (microcalcification and masses) of breast cancer cells makes it quite difficult for radiologists to diagnose it properly. Subsequently, …
View article: Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm
Optimal Cooperative Spectrum Sensing Based on Butterfly Optimization Algorithm Open
Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireles…
View article: EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning
EEG-Based Neonatal Sleep Stage Classification Using Ensemble Learning Open
Sleep stage classification can provide important information regarding neonatal brain development and maturation. Visual annotation, using polysomnography (PSG), is considered as a gold standard for neonatal sleep stage classification. How…
View article: A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video
A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video Open
Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake pattern, which functions as an essential indicator of neurophysiological organization in the neonatal period, has profound meaning in the prediction of …
View article: Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?
Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification? Open