304 citations · 357 across the 16 of their papers we have counts for
17 papers
Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models
Yuefeng Peng, Parnian Afshar, Megan Ganji +4
Large language models may encode sensitive information or outdated knowledge that needs to be removed, to ensure responsible and compliant model responses. Unlearning has emerged a…
Improving the Accuracy of Beauty Product Recommendations by Assessing Face Illumination Quality
Parnian Afshar, Jenny Yeon, Andriy Levitskyy +2
We focus on addressing the challenges in responsible beauty product recommendation, particularly when it involves comparing the product's color with a person's skin tone, such as f…
Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction
Sadaf Khademi, Shahin Heidarian, Parnian Afshar +4
The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT)…
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis +22
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor. Human-centered segmentation, which i…
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans
Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou +2
Lung cancer is the leading cause of mortality from cancer worldwide and has various histologic types, among which Lung Adenocarcinoma (LUAC) has recently been the most prevalent on…
Robust Framework for COVID-19 Identification from a Multicenter Dataset of Chest CT Scans
Sadaf Khademi, Shahin Heidarian, Parnian Afshar +8
The objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on chest CT sca…
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee +5
Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making…
Human-level COVID-19 Diagnosis from Low-dose CT Scans Using a Two-stage Time-distributed Capsule Network
Parnian Afshar, Moezedin Javad Rafiee, Farnoosh Naderkhani +8
Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negati…
Diagnosis/Prognosis of COVID-19 Images: Challenges, Opportunities, and Applications
Arash Mohammadi, Yingxu Wang, Nastaran Enshaei +7
The novel Coronavirus disease, COVID-19, has rapidly and abruptly changed the world as we knew in 2020. It becomes the most unprecedent challenge to analytic epidemiology in genera…
CT-CAPS: Feature Extraction-based Automated Framework for COVID-19 Disease Identification from Chest CT Scans using Capsule Networks
Shahin Heidarian, Parnian Afshar, Arash Mohammadi +4
The global outbreak of the novel corona virus (COVID-19) disease has drastically impacted the world and led to one of the most challenging crisis across the globe since World War I…
COVID-FACT: A Fully-Automated Capsule Network-based Framework for Identification of COVID-19 Cases from Chest CT scans
Shahin Heidarian, Parnian Afshar, Nastaran Enshaei +8
The newly discovered Corona virus Disease 2019 (COVID-19) has been globally spreading and causing hundreds of thousands of deaths around the world as of its first emergence in late…
COVID-CT-MD: COVID-19 Computed Tomography (CT) Scan Dataset Applicable in Machine Learning and Deep Learning
Parnian Afshar, Shahin Heidarian, Nastaran Enshaei +7
Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 1 million lives, since its emergence in late 2019. This high…
MIXCAPS: A Capsule Network-based Mixture of Experts for Lung Nodule Malignancy Prediction
Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou +3
Lung diseases including infections such as Pneumonia, Tuberculosis, and novel Coronavirus (COVID-19), together with Lung Cancer are significantly widespread and are, typically, con…
COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images
Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani +3
Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely contagious…
Capsule Networks for Brain Tumor Classification based on MRI Images and Course Tumor Boundaries
Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
According to official statistics, cancer is considered as the second leading cause of human fatalities. Among different types of cancer, brain tumor is seen as one of the deadliest…
From Hand-Crafted to Deep Learning-based Cancer Radiomics: Challenges and Opportunities
Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis +2
Recent advancements in signal processing and machine learning coupled with developments of electronic medical record keeping in hospitals and the availability of extensive set of m…
Brain Tumor Type Classification via Capsule Networks
Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis
Brain tumor is considered as one of the deadliest and most common form of cancer both in children and in adults. Consequently, determining the correct type of brain tumor in early…