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Sadaf Khademi

2 accepted papers

2025

SOLVE: Spatially Optimized Lung Volume Evidence Model for Efficient Nodule Malignancy Classification

ICASSP 2025accepted

Lung cancer diagnosis remains a critical challenge in personalized medicine, demanding novel approaches for efficient and accurate prediction. In this context, we propose the Spatially Optimized Lung Volume Evidence (SOLVE) framework, which is a novel lung malignancy prediction model developed by in…

Cited by 0SourceScholar
2023

Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers for Lung Cancer Malignancy Prediction

ICASSP 2023accepted

The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT) slices to predict Lung Adenocarcinoma (LUAC) malignancy with minimum expert involvement. Lung cancer is the leading caus…

Cited by 0SourceScholar