Sheida Nabavi

According to our database, Sheida Nabavi authored at least 43 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A multimodal graph neural network framework for cancer molecular subtype classification.

Bingjun Li, Sheida Nabavi

BMC Bioinform., December, 2024

Multi-modal Spatial Clustering for Spatial Transcriptomics Utilizing High-resolution Histology Images.

Bingjun Li, Mostafa Karami, Masum Shah Junayed, Sheida Nabavi

CoRR, 2024

Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms.

Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi

Comput. Medical Imaging Graph., 2024

Weakly-supervised deep learning model for prostate cancer diagnosis and Gleason grading of histopathology images.

Mohammad Mahdi Behzadi, Mohammad Madani, Hanzhang Wang, Jun Bai, Ankit Bhardwaj, Anna Tarakanova, Harold Yamase, Ga Hie Nam, Sheida Nabavi

Biomed. Signal Process. Control., 2024

Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing.

Samson Weiner, Bingjun Li, Sheida Nabavi

Bioinform., 2024

DCCNV: Enhanced CNV Detection in Single-Cell Sequencing Using Diffusion Process and Contrastive Learning.

Mostafa Karami, Bingjun Li, Samson Weiner, Sahand Hamzehei, Sheida Nabavi

Proceedings of the 15th ACM International Conference on Bioinformatics, 2024

CAPTURE: A Clustered Adaptive Patchwork Technique for Unified Registration Enhancement in Biological Imaging.

Sahand Hamzehei, Gianna Raimondi, Mostafa Karami, Linnaea Ostroff, Sheida Nabavi

Proceedings of the 15th ACM International Conference on Bioinformatics, 2024

2023

Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms.

Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi

CoRR, 2023

A Scaled Denoising Attention-Based Transformer for Breast Cancer Detection and Classification.

Masum Shah Junayed, Sheida Nabavi

Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller.

Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding

Proceedings of the 24th International Symposium on Quality Electronic Design, 2023

scGEMOC, A Graph Embedded Contrastive Learning Single-cell Multiomics Clustering Model.

Bingjun Li, Sheida Nabavi

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Contrastive Learning in Single-cell Multiomics Clustering.

Bingjun Li, Sheida Nabavi

Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection.

Sahand Hamzehei, Jun Bai, Gianna Raimondi, Rebecca Tripp, Linnaea Ostroff, Sheida Nabavi

Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

2022

Semi-supervised classification of disease prognosis using CR images with clinical data structured graph.

Jun Bai, Bingjun Li, Sheida Nabavi

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

Applying graph convolution neural network in digital breast tomosynthesis for cancer classification.

Jun Bai, Annie Jin, Andre Jin, Tianyu Wang, Clifford Yang, Sheida Nabavi

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

2021

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review.

Jun Bai, Russell Posner, Tianyu Wang, Clifford Yang, Sheida Nabavi

Medical Image Anal., 2021

Single-cell classification using graph convolutional networks.

Tianyu Wang, Jun Bai, Sheida Nabavi

BMC Bioinform., 2021

Single-cell RNA sequencing data clustering using graph convolutional networks.

Tianyu Wang, Bingjun Li, Sheida Nabavi

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Copy number variation detection using single cell sequencing data.

Fatima Zare, Jacob Stark, Sheida Nabavi

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

Cancer molecular subtype classification by graph convolutional networks on multi-omics data.

Bingjun Li, Tianyu Wang, Sheida Nabavi

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

2020

Preprocessing Sequence Coverage Data for More Precise Detection of Copy Number Variations.

Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Convolutional neural network for automated mass segmentation in mammography.

Dina Abdelhafiz, Jinbo Bi, Reda Ammar, Clifford Yang, Sheida Nabavi

BMC Bioinform., 2020

Integrative Deep Learning for PanCancer Molecular Subtype Classification Using Histopathological Images and RNAseq Data.

Fatima Zare, Javad Noorbakhsh, Tianyu Wang, Jeffrey H. Chuang, Sheida Nabavi

Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

2019

Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data.

Tianyu Wang, Boyang Li, Craig E. Nelson, Sheida Nabavi

BMC Bioinform., 2019

Deep convolutional neural networks for mammography: advances, challenges and applications.

Dina Abdelhafiz, Clifford Yang, Reda Ammar, Sheida Nabavi

BMC Bioinform., 2019

Single-cell RNAseq Imputation Based on Matrix Completion with Side Information.

Tianyu Wang, Sheida Nabavi

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Copy Number Variation Detection Using Total Variation.

Fatima Zare, Sheida Nabavi

Proceedings of the 10th ACM International Conference on Bioinformatics, 2019

Residual Deep Learning System for Mass Segmentation and Classification in Mammography.

Dina Abdelhafiz, Sheida Nabavi, Reda Ammar, Clifford Yang, Jinbo Bi

Proceedings of the 10th ACM International Conference on Bioinformatics, 2019

2018

Noise cancellation using total variation for copy number variation detection.

Fatima Zare, Abdelrahman Hosny, Sheida Nabavi

BMC Bioinform., 2018

Copy number variation detection using partial alignment information.

Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Predictive Meta-analysis of Multiple Microarray Datasets: An Application to Classification of Malignant Gliomas.

Nurislam Tursynbek, Ghazal Ghahramany, Sheida Nabavi, Amin Zollanvari

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Single-cell Clustering Based on Word Embedding and Nonparametric Methods.

Tianyu Wang, Sheida Nabavi

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data.

Fatima Zare, Michelle Dow, Nicholas Monteleone, Abdelrahman Hosny, Sheida Nabavi

BMC Bioinform., 2017

Survey on deep convolutional neural networks in mammography.

Dina Abdelhafiz, Sheida Nabavi, Reda Ammar, Clifford Yang

Proceedings of the 7th IEEE International Conference on Computational Advances in Bio and Medical Sciences, 2017

Noise cancellation for robust copy number variation detection using next generation sequencing data.

Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Differential gene expression analysis in single-cell RNA sequencing data.

Tianyu Wang, Sheida Nabavi

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Bias and Noise Cancellation for Robust Copy Number Variation Detection.

Fatima Zare, Sardar Ansari, Kayvan Najarian, Sheida Nabavi

Proceedings of the 8th ACM International Conference on Bioinformatics, 2017

Varsimlab: A Docker-based Pipeline to Automatically Synthesize Short Reads with Genomic Aberrations.

Abdelrahman Hosny, Fatima Zare, Sheida Nabavi

Proceedings of the 8th ACM International Conference on Bioinformatics, 2017

2016

EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes.

Sheida Nabavi, Daniel Schmolze, Mayinuer Maitituoheti, Sadhika Malladi, Andrew H. Beck

Bioinform., 2016

2015

Earth mover's distance for differential analysis of heterogeneous genomics data.

Sheida Nabavi, Andrew H. Beck

Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

2010

An Analytical Approach for Performance Evaluation of Bit-Patterned Media Channels.

Sheida Nabavi, Seungjune Jeon, B. V. K. Vijaya Kumar

IEEE J. Sel. Areas Commun., 2010

2008

Mitigating the Effects of Track Mis-Registration in Bit-Patterned Media.

Sheida Nabavi, B. V. K. Vijaya Kumar, James A. Bain

Proceedings of IEEE International Conference on Communications, 2008

2007

Two-Dimensional Generalized Partial Response Equalizer for Bit-Patterned Media.

Sheida Nabavi, B. V. K. Vijaya Kumar

Proceedings of IEEE International Conference on Communications, 2007