Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Asif Karim, Sami Azam et al.
Introduction An automated computerized approach can aid radiologists in the early diagnosis of lung disease from video modalities. This study focuses on the difficulties associated with identifying and categorizing respiratory diseases, including COVID-19, influenza, and pneumonia. Methods We propos...
Md. Abdur Rahman, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Mirjam Jonkman et al.
Abstract Skin cancer, a severe health threat, can spread rapidly if undetected. Therefore, early detection can lead to an advanced and efficient diagnosis, thus reducing mortality. Unsupervised classification techniques analyse extensive skin image datasets, identifying patterns and anomalies withou...
Mohaimenul Azam Khan Raiaan, Abdullah Al Mamun, Md. Adnanul Islam, Mohammed Eunus Ali et al.
Envy is often considered a negative trait in human behavior. However, envy also has a positive insight that can motivate a person to accomplish her desired goals. In this paper, we propose a novel method to identify a user’s state of envy (i.e., benign or malicious) based on features from her photos...
Sadman Sakib, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Md. Anisur Rahman et al.
Social media profile photos can demonstrate a variety of information about a person, including her personality, behavior, preference, individuality, and gender. Prediction of gender from social media photos has a number of real life applications such as gender marketing and identification of camoufl...
Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Mirjam Jonkman, Sheikh Mohammed Shariful Islam et al.
Accurate and early identification of gastrointestinal (GI) lesions is crucial for treating and preventing GI diseases, including cancer. Automated computer-aided diagnosis methods can assist physicians in early and accurate detection. Video classification of GI endoscopic videos is challenging due t...
Md. Saddam Hossain Mukta, Jubaer Ahmed, Mohaimenul Azam Khan Raiaan, Nur Mohammad Fahad et al.
Abstract 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 pursu...
Mohammad Azad, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Tanvir Rahman Anik et al.
Background and Objectives: Diffusion models, as a recent advancement in generative modeling, have become central to high-resolution image synthesis and reconstruction. Their rapid progress has notably shaped computer vision and health informatics, particularly by enhancing medical imaging and diagno...
Humaira Noor, Niful Islam, Md. Saddam Hossain Mukta, Nur Shazwani Kamarudin et al.
Node classification in complex networks plays an important role including social network analysis and recommendation systems. Some graph neural networks such as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) have emerged as effective approaches for achieving high-performance c...
Mohaimenul Azam Khan Raiaan, Md Abdur Rahman, Sami Azam, Kheng Cher Yeo et al.
Accurate and efficient multi-organ segmentation is crucial for clinical workflows, requiring high accuracy and reduced computational time. In this research, we propose a 3D diffusion-based knowledge distillation framework (3DKD-DiffuseNet) for multi-organ segmentation to achieve higher accuracy with...
Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Arefin Ittesafun Abian, Ripon Kumar Debnath et al.
The analysis of blood, including red blood cells (RBC) and different types of white blood cells (WBCs) plays a major role in the diagnosis of certain diseases. Automated segmentation of blood cells and their components can assist clinicians in effectively making diagnoses; however, it is quite chall...
Sadman Sakib, Mohaimenul Azam Khan Raiaan, Nur Mohammad Fahad, Md. Saddam Hossain Mukta et al.
The advancement of technology has led to a significant rise in cybercriminal activities, with ransomware emerging as a prominent threat to both individuals and businesses. Ransomware attacks involve encrypting a victim's data or entire computer system and then demanding a ransom payment in exchange ...
Arefin Ittesafun Abian, Ripon Kumar Debnath, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan et al.
Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures, variability in tumor appearance, and limited annotated data. To address these issues, we introduce Hyperbolic-convolut...
Musarrat Zeba, Abdullah‐Al Mamun, Kishoar Jahan Tithee, Debopom Sutradhar et al.
In healthcare, it is essential for any LLM-generated output to be reliable and accurate, particularly in cases involving decision-making and patient safety. However, the outputs are often unreliable in such critical areas due to the risk of hallucinated outputs from the LLMs. To address this issue, ...
Arefin Ittesafun Abian, Ripon Kumar Debnath, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan et al.
Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures, variability in tumor appearance, and limited annotated data. To address these issues, we introduce Hyperbolic-convolut...
Jubair Ahmed, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam
Colorectal liver metastases (CRLM) are a significant challenge in oncology, as recurrence after liver resection is frequently observed. Accurate prediction of CRLM recurrence is important to guide specific treatment strategies and improve clinical outcomes. To address this issue, this study proposes...