Sheida Nabavi

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 38

Top Topics

Microarray Datasets

Top Venues

Publications

Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi
Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms. Comput. Medical Imaging Graph. 113 (2024)
Mohammad Mahdi Behzadi, Mohammad Madani, Hanzhang Wang, Jun Bai, Ankit Bhardwaj, Anna Tarakanova, Harold Yamase, Ga Hie Nam, Sheida Nabavi
Weakly-supervised deep learning model for prostate cancer diagnosis and Gleason grading of histopathology images. Biomed. Signal Process. Control. 95 (2024)
Bingjun Li, Sheida Nabavi
A multimodal graph neural network framework for cancer molecular subtype classification. BMC Bioinform. 25 (1) (2024)
Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding
A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. ISQED (2023)
Sahand Hamzehei, Jun Bai, Gianna Raimondi, Rebecca Tripp, Linnaea Ostroff, Sheida Nabavi
3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection. BCB (2023)
Bingjun Li, Sheida Nabavi
Contrastive Learning in Single-cell Multiomics Clustering. BCB (2023)
Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi
Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms. CoRR (2023)
Bingjun Li, Sheida Nabavi
scGEMOC, A Graph Embedded Contrastive Learning Single-cell Multiomics Clustering Model. BIBM (2023)
Masum Shah Junayed, Sheida Nabavi
A Scaled Denoising Attention-Based Transformer for Breast Cancer Detection and Classification. MLMI@MICCAI (2) (2023)
Bingjun Li, Sheida Nabavi
A Multimodal Graph Neural Network Framework for Cancer Molecular Subtype Classification. CoRR (2023)
Jun Bai, Annie Jin, Andre Jin, Tianyu Wang, Clifford Yang, Sheida Nabavi
Applying graph convolution neural network in digital breast tomosynthesis for cancer classification. BCB (2022)
Jun Bai, Bingjun Li, Sheida Nabavi
Semi-supervised classification of disease prognosis using CR images with clinical data structured graph. BCB (2022)
Mohammad Mahdi Behzadi, Mohammad Madani, Hanzhang Wang, Jun Bai, Ankit Bhardwaj, Anna Tarakanova, Harold Yamase, Ga Hie Nam, Sheida Nabavi
Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images. CoRR (2022)
Fatima Zare, Jacob Stark, Sheida Nabavi
Copy number variation detection using single cell sequencing data. BCB (2021)
Tianyu Wang, Jun Bai, Sheida Nabavi
Single-cell classification using graph convolutional networks. BMC Bioinform. 22 (1) (2021)
Bingjun Li, Tianyu Wang, Sheida Nabavi
Cancer molecular subtype classification by graph convolutional networks on multi-omics data. BCB (2021)
Jun Bai, Russell Posner, Tianyu Wang, Clifford Yang, Sheida Nabavi
Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review. Medical Image Anal. 71 (2021)
Tianyu Wang, Bingjun Li, Sheida Nabavi
Single-cell RNA sequencing data clustering using graph convolutional networks. BIBM (2021)
Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi
Preprocessing Sequence Coverage Data for More Precise Detection of Copy Number Variations. IEEE ACM Trans. Comput. Biol. Bioinform. 17 (3) (2020)
Dina Abdelhafiz, Jinbo Bi, Reda Ammar, Clifford Yang, Sheida Nabavi
Convolutional neural network for automated mass segmentation in mammography. BMC Bioinform. (1) (2020)
Fatima Zare, Javad Noorbakhsh, Tianyu Wang, Jeffrey H. Chuang, Sheida Nabavi
Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data. BCB (2020)
Fatima Zare, Sheida Nabavi
Copy Number Variation Detection Using Total Variation. BCB (2019)
Dina Abdelhafiz, Sheida Nabavi, Reda Ammar, Clifford Yang, Jinbo Bi
Residual Deep Learning System for Mass Segmentation and Classification in Mammography. BCB (2019)
Dina Abdelhafiz, Clifford Yang, Reda Ammar, Sheida Nabavi
Deep convolutional neural networks for mammography: advances, challenges and applications. BMC Bioinform. (11) (2019)
Tianyu Wang, Boyang Li, Craig E. Nelson, Sheida Nabavi
Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data. BMC Bioinform. 20 (1) (2019)
Tianyu Wang, Sheida Nabavi
Single-cell RNAseq Imputation Based on Matrix Completion with Side Information. BIBM (2019)
Tianyu Wang, Sheida Nabavi
Single-cell Clustering Based on Word Embedding and Nonparametric Methods. BCB (2018)
Fatima Zare, Abdelrahman Hosny, Sheida Nabavi
Noise cancellation using total variation for copy number variation detection. BMC Bioinform. (11) (2018)
Dina Abdelhafiz, Sheida Nabavi, Reda Ammar, Clifford Yang, Jinbo Bi
Convolutional Neural Network for Automated Mass Segmentation in Mammography. ICCABS (2018)
Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi
Copy number variation detection using partial alignment information. BIBM (2018)
Nurislam Tursynbek, Ghazal Ghahramany, Sheida Nabavi, Amin Zollanvari
Predictive Meta-analysis of Multiple Microarray Datasets: An Application to Classification of Malignant Gliomas. BIBM (2018)
Dina Abdelhafiz, Sheida Nabavi, Reda Ammar, Clifford Yang
Survey on deep convolutional neural networks in mammography. ICCABS (2017)
Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi
Bias and Noise Cancellation for Robust Copy Number Variation Detection. BCB (2017)
Fatima Zare, Michelle Dow, Nicholas Monteleone, Abdelrahman Hosny, Sheida Nabavi
An evaluation of copy number variation detection tools for cancer using whole exome sequencing data. BMC Bioinform. 18 (1) (2017)
Tianyu Wang, Sheida Nabavi
Differential gene expression analysis in single-cell RNA sequencing data. BIBM (2017)
Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi
Noise cancellation for robust copy number variation detection using next generation sequencing data. BIBM (2017)
Abdelrahman Hosny, Fatima Zare, Sheida Nabavi
Varsimlab: A Docker-based Pipeline to Automatically Synthesize Short Reads with Genomic Aberrations. BCB (2017)
Sheida Nabavi, Daniel Schmolze, Mayinuer Maitituoheti, Sadhika Malladi, Andrew H. Beck
EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes. Bioinform. 32 (4) (2016)
Sheida Nabavi, Andrew H. Beck
Earth mover's distance for differential analysis of heterogeneous genomics data. GlobalSIP (2015)
Sheida Nabavi, Seungjune Jeon, B. V. K. Vijaya Kumar
An Analytical Approach for Performance Evaluation of Bit-Patterned Media Channels. IEEE J. Sel. Areas Commun. 28 (2) (2010)
Sheida Nabavi, B. V. K. Vijaya Kumar, James A. Bain
Mitigating the Effects of Track Mis-Registration in Bit-Patterned Media. ICC (2008)
Sheida Nabavi, B. V. K. Vijaya Kumar
Two-Dimensional Generalized Partial Response Equalizer for Bit-Patterned Media. ICC (2007)