2 citations · 3 across the 7 of their papers we have counts for
7 papers
DECODE: Dual-Enhanced Conditioned Diffusion for EEG Forecasting
Mehran Shabanpour, Sadaf Khademi, Konstantinos N Plataniotis +1
Forecasting Electroncephalography (EEG) signals during cognitive events remains a fundamental challenge in neuroscience and Brain-Computer Interfaces (BCIs), as existing methods st…
AutoRad-Lung: A Radiomic-Guided Prompting Autoregressive Vision-Language Model for Lung Nodule Malignancy Prediction
Sadaf Khademi, Mehran Shabanpour, Reza Taleei +2
Lung cancer remains one of the leading causes of cancer-related mortality worldwide. A crucial challenge for early diagnosis is differentiating uncertain cases with similar visual…
MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition
Mehran Shabanpour, Kasra Rad, Sadaf Khademi +1
High-Density surface Electromyography (HDsEMG) has emerged as a pivotal resource for Human-Computer Interaction (HCI), offering direct insights into muscle activities and motion in…
FH-TabNet: Multi-Class Familial Hypercholesterolemia Detection via a Multi-Stage Tabular Deep Learning
Sadaf Khademi, Zohreh Hajiakhondi, Golnaz Vaseghi +2
Familial Hypercholesterolemia (FH) is a genetic disorder characterized by elevated levels of Low-Density Lipoprotein (LDL) cholesterol or its associated genes. Early-stage and accu…
NYCTALE: Neuro-Evidence Transformer for Adaptive and Personalized Lung Nodule Invasiveness Prediction
Sadaf Khademi, Anastasia Oikonomou, Konstantinos N. Plataniotis +1
Drawing inspiration from the primate brain's intriguing evidence accumulation process, and guided by models from cognitive psychology and neuroscience, the paper introduces the NYC…
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)…
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…