Sami Azam

Charles Darwin University | CDU · Faculty of Science and Technology

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 conditions. In this paper, human retinal OCT images a...

This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based framework employs two publicly available lung CT scan datasets which are...

People exhibit unique emotional responses. In the same scenario, the emotional reactions of two individuals can be either similar or vastly different. For instance, consider one person's reaction to an invitation to smoke versus another person's response to a query about their sleep quality. The identification of these individual traits through the...

People exhibit unique emotional responses. In the same scenario, the emotional reactions of two individuals can be either similar or vastly different. For instance, consider one person's reaction to an invitation to smoke versus another person's response to a query about their sleep quality. The identification of these individual traits through the...

Colorectal cancer (CRC) is characterized by the uncontrollable growth of cancerous cells within the rectal mucosa. In contrast, colon polyps, precancerous growths, can develop into colon cancer, causing symptoms like rectal bleeding, abdominal pain, diarrhea, weight loss, and constipation. It is the leading cause of death worldwide, and this potent...

Almost 85% of companies polled said they were looking into anomaly detection (AD) technologies for their industrial image anomalies. The present problem concerns detecting anomalies often occupied by redundant data. It can be either in images or in videos. Finding a correct pattern is a challenging task. AD is crucial for various applications, incl...

This paper proposes a hybrid approach using design science research to identify rogue RF transmitters and locate their targets. We engineered a framework to identify masquerading attacks indicating the presence of multiple adversaries posing as a single node. We propose a methodology based on spatial correlation calculated from received signal stre...

The increasing incidence of skin cancer necessitates advancements in early detection methods, where deep learning can be beneficial. This study introduces SkinNet-14, a novel deep learning model designed to classify skin cancer types using low-resolution dermoscopy images. Unlike existing models that require high-resolution images and extensive tra...

Recent advancements in natural language processing (NLP) have led to automation in various domains. However, clinical NLP often relies on benchmark datasets that may not reflect real-world scenarios accurately. Automatic ICD coding, a vital NLP task, typically uses outdated and imbalanced datasets like MIMIC-III, with existing methods yielding micr...

Ischemic heart disease (IHD) is one of the leading causes of death worldwide. However, different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of people. This study examines the current IHD condition in southern Bangladesh, a Southeast Asian middle-income country. The main approac...

The diagnosis of bronchiectasis requires measuring abnormal bronchial dilation. It is confirmed using a chest CT scan, where the key feature is an increased broncho-arterial ratio (BAR) (>0.8 in children), often with bronchial wall thickening. Image processing methods facilitate quicker interpretation and detailed evaluations by lobes and segments....

In this digital era, users frequently share their thoughts, preferences, and ideas through social media, which reflect their Basic Human Values. Basic Human Values (aka values) are the fundamental aspects of human behavior, which define what we consider important, and worth having and pursue them. Existing studies identify the values of individuals...

Skin cancer is a major concern to public health, accounting for one-third of the reported cancers. If not detected early, the cancer has the potential for severe consequences. Recognizing the critical need for effective skin cancer classification, we address the limitations of existing models, which are often too large to deploy in areas with limit...

The rapidly expanding Internet of Medical Things (IoMT) landscape fosters enormous opportunities for personalized healthcare, yet it also exposes patients and healthcare systems to diverse security threats. Heterogeneous IoMT devices present challenges that need comprehensive risk assessment due to their varying functionality, protocols, and vulner...

Objective Early diagnosis of breast cancer can lead to effective treatment, possibly increase long-term survival rates, and improve quality of life. The objective of this study is to present an automated analysis and classification system for breast cancer using clinical markers such as tumor shape, orientation, margin, and surrounding tissue. The...

The automatic assessment of perceived image quality is crucial in the field of image processing. To achieve this idea, we propose an image quality assessment (IQA) method for blurriness. The features of gradient and singular value were extracted in this method instead of the single feature in the traditional IQA algorithms. According to the insuffi...

This paper examines the role of Generative AI (GenAI) and Large Language Models (LLMs) in penetration testing exploring the benefits, challenges, and risks associated with cyber security applications. Through the use of generative artificial intelligence, penetration testing becomes more creative, test environments are customised, and continuous le...

A novel automated multi-classification approach is proposed for the anticipation of lung abnormalities using chest X-ray and CT images. The study leverages a publicly accessible dataset with an insufficient and unbalanced number of images, addressing this issue by employing the data augmentation approach DCGAN to balance the dataset. Various prepro...

Cervical cancer is a prevalent disease affecting the cervix cells in women and is one of the leading causes of mortality for women globally. The Pap smear test determines the risk of cervical cancer by detecting abnormal cervix cells. Early detection and diagnosis of this cancer can effectively increase the patient’s survival rate. The advent of ar...

This study proposes a novel approach for breast tumor classification from ultrasound images into benign and malignant by converting the region of interest (ROI) of a 2D ultrasound image into a 3D representation using the point-e system, allowing for in-depth analysis of underlying characteristics. Instead of relying solely on 2D imaging features, t...

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 features, which align with the clinical markers used by...

Large Language Models (LLMs) recently demonstrated extraordinary capability, including natural language processing (NLP), language translation, text generation, question answering, etc. Moreover, LLMs are a new and essential part of computerized language processing, having the ability to understand complex verbal patterns and generate coherent and...

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 when brain growth is rapid, resulting in poor spee...

Bronchiectasis is a chronic respiratory disorder characterized by the dilation and damage of bronchial walls due to recurrent and prolonged episodes of inflammation and infection. The diagnosis of bronchiectasis requires objective measurement of abnormal bronchial dilation. It is confirmed radiologically using a chest tomography (C.T.). scan where...

In today's fast-paced world, everyone wants things to happen quickly. Thanks to the internet, news spreads super fast. But not all news is important. News summarization helps by giving a short version of each news story, so readers can easily figure out what type of news they want to read. There are two main types of summarization: Abstractive Text...

In the rapidly developing world of the Internet of Things (IoT), data security has become increasingly important since massive personal data are collected. IoT devices have resource constraints, which makes traditional cryptographic algorithms ineffective for securing IoT devices. To overcome resource limitations, lightweight cryptographic algorith...

COVID-19, pneumonia, and tuberculosis have had a significant effect on recent global health. Since 2019, COVID-19 has been a major factor underlying the increase in respiratory-related terminal illness. Early-stage interpretation and identification of these diseases from X-ray images is essential to aid medical specialists in diagnosis. In this stu...

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 significant features. Method Ten informative featu...

In this study, we propose machine learning (ML) for risk factors analysis and survival prediction of Heart Failure (HF) patients using a survival dataset. Five supervised ML methods are applied to the dataset: Decision Tree (DT), Decision Tree Regressor (DTR), Random Forest (RF), XGBoost, and Gradient Boosting (GB) algorithms. We compare the applie...

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 regard, early diagnosis of KOA is necessary for better...

Introduction Breast cancer stands as the second most deadly form of cancer among women worldwide. Early diagnosis and treatment can significantly mitigate mortality rates. Purpose The study aims to classify breast ultrasound images into benign and malignant tumors. This approach involves segmenting the breast's region of interest (ROI) employing a...

p>Large Language Models (LLMs) recently demonstrated extraordinary capability, including natural language processing (NLP), language translation, text generation, question answering, etc. Moreover, LLMs are a new and essential part of computerized language processing, having the ability to understand complex verbal patterns and generate coherent an...

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 in a sentence. Numerous architectures have demons...

Large Language Models (LLMs) recently demonstrated extraordinary capability, including natural language processing (NLP), language translation, text generation, question answering, etc. Moreover, LLMs are a new and essential part of computerized language processing, having the ability to understand complex verbal patterns and generate coherent and...

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 supervised learning. As the quantity of documents grows, the performance of classic supervised classifiers has deteri...

The selection of features for text classification is a fundamental task in text mining and information retrieval. Despite being the sixth most widely spoken language in the world, Bangla has received little attention due to the scarcity of text datasets. In this research, we collected, annotated, and prepared a comprehensive dataset of 212,184 Bang...

With the development of computer vision and deep learning technologies, rapidly expanding approaches have been introduced that allow anyone to create videos and pictures that are both phony and incredibly lifelike. The term deepfake methodology is used to describe such technologies. Face alteration can be performed both in videos and pictures with...

the recognition of Hand gestures has become a critical point as it is widely used in everyday applications. the challenge in this is to improve the recognition effect and develop a fast recognition method. Glove and led-based methods involve external devices in detecting and interpreting hand gestures, making human-computer interaction less natural...

The Rise of the Internet of Things (IoT) technology made the world smarter as it has embedded deeply in several application areas such as manufacturing, homes, cities, and health etc. In the developed cities, millions of IoT devices are deployed to enhance the lifestyle of citizens. IoT devices increases the efficiency and productivity with time an...

Hearing loss is a prevalent health issue that affects individuals worldwide. Binaural hearing refers to the ability to integrate information received simultaneously from both ears, allowing individuals to identify, locate, and separate sound sources. Auditory evoked potentials (AEPs) refer to the electrical responses that are generated within any p...

The binaural masking level difference (BMLD) is a psychoacoustic method to determine binaural interaction and central auditory processes. The BMLD is the difference in hearing thresholds in homophasic and antiphasic conditions. The duration, phase and frequency of the stimuli can affect the BMLD. The main aim of the study is to evaluate the BMLD fo...

Bronchiectasis in children can progress to a severe lung condition if not diagnosed and treated early. The radiological diagnostic criteria for the diagnosis of bronchiectasis is an increased broncho-arterial (BA) ratio. From high-resolution computed tomography (HRCT) scans, the BA pairs must be detected first to derive the BA ratio. This study aim...

The privacy and security of patients' health records have been an ongoing issue, and researchers are in a race against technology to design a system that can help stop the compromising of patient data. Many researchers have proposed solutions; however, most solutions have not incorporated potential parameters that can ensure private and secure pers...

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 automated system for DR severity classification employing...

A fully automated system based on three-dimensional (3D) magnetic resonance imaging (MRI) scans for brain tumor segmentation could be a diagnostic aid to clinical specialists, as manual segmentation is challenging, arduous, tedious and error prone. Employing 3D convolutions requires large computational cost and memory capacity. This study proposes...

Almost 17.9 million people are losing their lives due to cardiovascular disease, which is 32% of total death throughout the world. It is a global concern nowadays. However, it is a matter of joy that the mortality rate due to heart disease can be reduced by early treatment, for which early-stage detection is a crucial issue. This study is aimed at...

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 CNN model. Convolutional layers provide diverse fe...

Menopause is an obligatory phenomenon in a woman’s life. Some women face mental and physical issues during their menopausal period. Depression is one of the issues some women struggle with during their menopausal period. The scarcity of specialists, lack of knowledge, and awareness is the motivating factor in this research to predict depression amo...

Privacy in Electronic Health Records (EHR) has become a significant concern in today’s rapidly changing world, particularly for personal and sensitive user data. The sheer volume and sensitive nature of patient records require healthcare providers to exercise an intense quantity of caution during EHR implementation. In recent years, various healthc...

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), Early MCI (EMCI), Late MCI (LMCI), and Alzheimer’s Disease (AD). Alzheimer’s disease is conventionally diagn...

The adaptation of the Internet of Medical Things (IoMT) has provided efficient and timely services and has transformed the healthcare industry to a great extent. Monitoring patients remotely and managing hospital records and data have become effortless with the advent of IoMT. However, security and privacy have become a significant concern with the...

Background: In today's society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death. Results: This research uses a network a...

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, Pulmonary Fibrosis, Nodule, and Consolidation, are studied from the ChestX-ray14 dataset. A proposed fine-tun...

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 be difficult to detect. Therefore, in this study, a...

If Diabetic Retinopathy (DR) patients do not receive quick diagnosis and treatment, they may lose vision. DR, an eye disorder caused by high blood glucose, is becoming more prevalent worldwide. Once early warning signs are detected, the severity of the disease must be validated before choosing the best treatment. In this research, a deep learning n...