463 citations · 2.3k across the 59 of their papers we have counts for
63 papers
SIGHT: A Methodological Appraisal Framework for Evaluating Large Language Models in Ophthalmology
Hadi Vahedi, Fatemeh Razmjooei, Farbod Semnani +3
Large language models (LLMs) are increasingly evaluated across ophthalmic tasks, yet the methodological quality of these evaluations has received little attention. Most studies rep…
The Role of Natural Language Understanding in Multimodal Video-Based Dengue Diagnosis
Danial Sharifrazi, Saadat Behzadi, Julakha Jahan Jui +5
Detecting infection-related behavioral changes in mosquitoes from video data is challenging because mosquitoes are small, move rapidly and irregularly, and are affected by environm…
A Hybrid Framework of Vision Transformer and Gated Recurrent Unit for Detection of Mosquito Diseases
Danial Sharifrazi, Saadat Behzadi, Nouman Javed +3
Identifying dengue virus-infected mosquitoes from control mosquitoes is a major challenge in analyzing mosquito locomotion behavior due to the small size and complexity of the vide…
NeuroStrata: An Electroencephalographic Connectivity-Aware Deep Representation Learning Framework for Dynamic Brain Network Analysis of Mental Stress
Sayantan Acharya, Hamzeh Asgharnezhad, Abbas Khosravi +3
This study introduces NeuroStrata, a connectivity-aware deep representation learning framework for EEG-based mental stress analysis using Time-Varying Partial Directed Coherence (T…
Towards Self-Evolving Agents: A Human-Inspired Adaptive Exploration-Exploitation Framework for Genetic Network Programming
Ali Kohan, Mohamad Roshanzamir, Roohallah Alizadehsani +1
Recent advancements in agentic AI have increasingly moved toward graph-based methods, driven by the demand for explainable, human-centered, and non-linear reasoning workflows. A pr…
Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability
Yuheng Liang, Lucy Chhuo, Ahmadreza Argha +9
Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of patients exhibit intrinsic or acquired resistance, making accurate pre-treatment…
A Q-learning-based QoS-aware multipath routing protocol in IoMT-based wireless body area network
Mehdi Hosseinzadeh, Roohallah Alizadehsani, Amin Beheshti +7
The Internet of Medical Things (IoMT) enables intelligent healthcare services but faces challenges such as dynamic topology, energy constraints, and diverse QoS requirements. This…
UCTECG-Net: Uncertainty-aware Convolution Transformer ECG Network for Arrhythmia Detection
Hamzeh Asgharnezhad, Pegah Tabarisaadi, Abbas Khosravi +2
Deep learning has improved automated electrocardiogram (ECG) classification, but limited insight into prediction reliability hinders its use in safety-critical settings. This paper…
SSI-GAN: Semi-Supervised Swin-Inspired Generative Adversarial Networks for Neuronal Spike Classification
Danial Sharifrazi, Nouman Javed, Mojtaba Mohammadi +5
Mosquitos are the main transmissive agents of arboviral diseases. Manual classification of their neuronal spike patterns is very labor-intensive and expensive. Most available deep…
Rewiring Human Brain Networks via Lightweight Dynamic Connectivity Framework: An EEG-Based Stress Validation
Sayantan Acharya, Abbas Khosravi, Douglas Creighton +2
In recent years, Electroencephalographic analysis has gained prominence in stress research when combined with AI and Machine Learning models for validation. In this study, a lightw…
No-Reference Image Contrast Assessment with Customized EfficientNet-B0
Javad Hassannataj Joloudari, Bita Mesbahzadeh, Omid Zare +3
Image contrast was a fundamental factor in visual perception and played a vital role in overall image quality. However, most no reference image quality assessment NR IQA models str…
Exploring the Relationships Between Physiological Signals During Automated Fatigue Detection
Kourosh Kakhi, Abbas Khosravi, Roohallah Alizadehsani +1
Fatigue detection using physiological signals is critical in domains such as transportation, healthcare, and performance monitoring. While most studies focus on single modalities,…
A Lightweight and Robust Framework for Real-Time Colorectal Polyp Detection Using LOF-Based Preprocessing and YOLO-v11n
Saadat Behzadi, Danial Sharifrazi, Bita Mesbahzadeh +2
Objectives: Timely and accurate detection of colorectal polyps plays a crucial role in diagnosing and preventing colorectal cancer, a major cause of mortality worldwide. This study…
A Quad-Step Approach to Uncertainty-Aware Deep Learning for Skin Cancer Classification
Hamzeh Asgharnezhad, Pegah Tabarisaadi, Abbas Khosravi +2
Accurate skin cancer diagnosis is vital for early treatment and improved patient outcomes. Deep learning (DL) models have shown promise in automating skin cancer classification, ye…
Enhancing Monte Carlo Dropout Performance for Uncertainty Quantification
Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani +2
Knowing the uncertainty associated with the output of a deep neural network is of paramount importance in making trustworthy decisions, particularly in high-stakes fields like medi…
A machine learning approach for Premature Coronary Artery Disease Diagnosis according to Different Ethnicities in Iran
Mohamad Roshanzamir, Roohallah Alizadehsani, Ehsan Zarepur +6
Premature coronary artery disease (PCAD) refers to the early onset of the disease, usually before the age of 55 for men and 65 for women. Coronary Artery Disease (CAD) develops whe…
Brain Ageing Prediction using Isolation Forest Technique and Residual Neural Network (ResNet)
Saadat Behzadi, Danial Sharifrazi, Roohallah Alizadehsani +2
Brain aging is a complex and dynamic process, leading to functional and structural changes in the brain. These changes could lead to the increased risk of neurodegenerative disease…
Fatigue Monitoring Using Wearables and AI: Trends, Challenges, and Future Opportunities
Kourosh Kakhi, Senthil Kumar Jagatheesaperumal, Abbas Khosravi +2
Monitoring fatigue is essential for improving safety, particularly for people who work long shifts or in high-demand workplaces. The development of wearable technologies, such as f…
Enhancing Multiagent Genetic Network Programming Performance Using Search Space Reduction
Ali Kohan, Mohamad Roshanzamir, Roohallah Alizadehsani
Genetic Network Programming (GNP) is an evolutionary algorithm that extends Genetic Programming (GP). It is typically used in agent control problems. In contrast to GP, which emplo…
Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder
Kamala Devi Kannan, Senthil Kumar Jagatheesaperumal, Rajesh N. V. P. S. Kandala +3
For the early identification, diagnosis, and treatment of mental health illnesses, the integration of deep learning (DL) and machine learning (ML) have started playing a significan…
Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review
Javad Hassannataj Joloudari, Mohammad Maftoun, Bahareh Nakisa +2
The Complex Emotion Recognition System (CERS) deciphers complex emotional states by examining combinations of basic emotions expressed, their interconnections, and the dynamic vari…
Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review
Danial Sharifrazi, Nouman Javed, Javad Hassannataj Joloudari +5
Human brain neuron activities are incredibly significant nowadays. Neuronal behavior is assessed by analyzing signal data such as electroencephalography (EEG), which can offer scie…
Radiomics and artificial Intelligence for thyroid cancer diagnosis: Concepts, challenges, and solutions
Milad Yousefi, Shadi Farabi Maleki, Hadi Vahedi +9
Thyroid cancer is an increasing global health concern that requires advanced diagnostic methods. The application of AI and radiomics to thyroid cancer diagnosis is examined in this…
Artificial Intelligence and Diabetes Mellitus: An Inside Look Through the Retina
Yasin Sadeghi Bazargani, Majid Mirzaei, Navid Sobhi +7
Diabetes mellitus (DM) predisposes patients to vascular complications. Retinal images and vasculature reflect the body's micro- and macrovascular health. They can be used to diagno…