168 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institute for Research in Fundamental SciencesIR5 papers
- Shahid Beheshti UniversityIR5 papers
- Icahn School of Medicine at Mount SinaiUS4 papers
- Indiana University – Purdue University IndianapolisUS4 papers
- Cedars-Sinai Medical CenterUS3 papers
- Child Health and Development InstituteUS3 papers
- Research Institute for Endocrine SciencesIR3 papers
- Sharif University of TechnologyIR3 papers
- Tehran University of Medical SciencesIR3 papers
- Arizona State UniversityUS2 papers
- Columbia UniversityUS2 papers
- Iran University of Medical SciencesIR2 papers
24 papers
Safety boundary maintenance in consumer AI systems responding to pediatric health queries: a cross-platform benchmark evaluation under naturalistic and adversarially pressured conditions
Vahideh Zolfaghari, Leila Mashhadi, Mitra Ahadi +2
Consumer artificial intelligence chatbots are now accessed by hundreds of millions of users seeking health information, yet systematic evaluation of their safety boundary maintenan…
Ultrasound-based detection and malignancy prediction of breast lesions eligible for biopsy: A multi-center clinical-scenario study using nomograms, large language models, and radiologist evaluation
Ali Abbasian Ardakani, Afshin Mohammadi, Taha Yusuf Kuzan +7
To develop and externally validate integrated ultrasound nomograms combining BIRADS features and quantitative morphometric characteristics, and to compare their performance with ex…
Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images
Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi +13
Introduction: This study provides a comprehensive performance assessment of vision-language models (VLMs) against established convolutional neural networks (CNNs) and classic machi…
Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models
Nariman Naderi, Seyed Amir Ahmad Safavi-Naini, Thomas Savage +4
This study evaluated self-reported response certainty across several large language models (GPT, Claude, Llama, Phi, Mistral, Gemini, Gemma, and Qwen) using 300 gastroenterology bo…
Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models
Seyed Amir Ahmad Safavi-Naini, Shuhaib Ali, Omer Shahab +15
Background and Aims: This study evaluates the medical reasoning performance of large language models (LLMs) and vision language models (VLMs) in gastroenterology. Methods: We used…
Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data
Mohammadreza Ghaffarzadeh-Esfahani, Mahdi Ghaffarzadeh-Esfahani, Arian Salahi-Niri +39
This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimension…
A Global Data-Driven Model for The Hippocampus and Nucleus Accumbens of Rat From The Local Field Potential Recordings (LFP)
Maedeh Sadeghi, Mahdi Aliyari Shoorehdeli, Shole jamali +1
In brain neural networks, Local Field Potential (LFP) signals represent the dynamic flow of information. Analyzing LFP clinical data plays a critical role in improving our understa…
Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response
Fatih Ozyurt, Jafar Majidpour, Tarik A. Rashid +2
The assessment of the well-being of the peripheral auditory nerve system in individuals experiencing hearing impairment is conducted through auditory brainstem response (ABR) testi…
Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis
Bahareh Morovati, Reza Lashgari, Mojtaba Hajihasani +1
Breast cancer is the second most common cancer among women worldwide. Diagnosis of breast cancer by the pathologists is a time-consuming procedure and subjective. Computer aided di…
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging
Ali Hashemi, Yijing Gao, Chang Cai +4
Several problems in neuroimaging and beyond require inference on the parameters of multi-task sparse hierarchical regression models. Examples include M/EEG inverse problems, neural…
Accurate and Rapid Diagnosis of COVID-19 Pneumonia with Batch Effect Removal of Chest CT-Scans and Interpretable Artificial Intelligence
Rassa Ghavami Modegh, Mehrab Hamidi, Saeed Masoudian +22
COVID-19 is a virus with high transmission rate that demands rapid identification of the infected patients to reduce the spread of the disease. The current gold-standard test, Reve…
Medical Imaging and Computational Image Analysis in COVID-19 Diagnosis: A Review
Shahabedin Nabavi, Azar Ejmalian, Mohsen Ebrahimi Moghaddam +4
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough,…
Graphene-TiS heterojunction for selective polar vapor sensing at room temperature
Nassim Rafiefard, Azam Iraji zad, Ali Esfandiar +5
In this work, the room temperature polar vapor sensing behavior of two dimentional (2D) heterojunction Graphene-TiS3 materials and TiS3 nanoribbons is investigated. TiS3 nanoribbon…
The Efficacy of Microaneurysms Detection With and Without Vessel Segmentation in Color Retinal Images
Meysam Tavakoli, Mahdieh Nazar, Alireza Mehdizadeh
Computer-Aided Diagnosis systems are required to extract suitable information about retina and its changes. In particular, identifying objects of interest such as lesions and anato…
Automated Optic Nerve Head Detection Based on Different Retinal Vasculature Segmentation Methods and Mathematical Morphology
Meysam Tavakoli, Mahdieh Nazar, Alireza Golestaneh +1
Computer vision and image processing techniques provide important assistance to physicians and relieve their workload in different tasks. In particular, identifying objects of inte…
Automated Detection of Microaneurysms in Color Fundus Images using Deep Learning with Different Preprocessing Approaches
Meysam Tavakoli, Sina Jazani, Mahdieh Nazar
Imaging methods by using computer techniques provide doctors assistance at any time and relieve their workload, especially for iterative processes like identifying objects of inter…
Automated Fovea Detection Based on Unsupervised Retinal Vessel Segmentation Method
Meysam Tavakoli, Patrick Kelley, Mahdieh Nazar +1
The Computer-Assisted Diagnosis systems could save workloads and give objective diagnostic to ophthalmologists. At first, feature extraction is a fundamental step. One of these ret…
Improving the Izhikevich Model Based on Rat Basolateral Amygdala and Hippocampus Neurons, and Recognizing Their Possible Firing Patterns
Sahar Hojjatinia, Mahdi Aliyari Shoorehdeli, Zahra Fatahi +2
Introduction- Identifying the potential firing patterns following different brain regions under normal and abnormal conditions increases our understanding of events at the level of…
Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning
Mostafa Nazari, Isaac Shiri, Ghasem Hajianfar +4
Purpose: To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cells renal cell carcinoma (ccRCC) grade. Methods…
Strain effect on quantum conductance of graphene nanoribbons from maximally localized Wannier functions
R. Rasuli, H. Rafii-Tabar, A. Iraji zad
Density functional study of strain effects on the electronic band structure and transport prop- erties of the graphene nanoribbons (GNR) is presented. We apply a uniaxial strain in…
Uniaxial strain on gapped graphene
M. Farjam, H. Rafii-Tabar
We study the effect of uniaxial strain on the electronic band structure of gapped graphene. We consider two types of gapped graphene, one which breaks the symmetry between the two…
Comment on "Band structure engineering of graphene by strain: First-principles calculations"
M. Farjam, H. Rafii-Tabar
In their first-principles calculations of the electronic band structure of graphene under uniaxial strain, Gui, Li, and Zhong [Phys. Rev. B \textbf{78}, 075435 (2008)] have found o…
Energy gap opening in submonolayer lithium on graphene: Local density functional and tight-binding calculations
M. Farjam, H. Rafii-Tabar
The adsorption of an alkali-metal submonolayer on graphene occupying every third hexagon of the honeycomb lattice in a commensurate arrangement…
Enhanced roughness of lipid membranes caused by external electric fields
M Neek-Amal, H. Rafii-Tabar, H. R. Sepangi
The behavior of lipid membranes in the presence of an external electric field is studied and used to examine the influence of such fields on membrane parameters such as roughness a…