Publications by authors named "Sheida Nabavi"

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Hybrid transformer-based model for mammogram classification by integrating prior and current images.
Afsana Ahsan Jeny, Sahand Hamzehei, Annie Jin, Stephen Andrew Baker, Tucker Van Rathe, Sheida Nabavi

Med Phys· May 2025

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Advanced Feature Extraction and Outlier Detection for 3D Biological/Biomedical Image Registration.
Sahand Hamzehei, Jun Bai, Gianna Raimondi, Rebecca Tripp, Linnaea Ostroff, Sheida Nabavi

IEEE Trans Comput Biol Bioinform· January 2025

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CAPTURE: A Clustered Adaptive Patchwork Technique for Unified Registration Enhancement in Biological Imaging.
Sahand Hamzehei, Gianna Raimondi, Mostafa Karami, Linnaea Ostroff, Sheida Nabavi

ACM BCB· December 2024

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Benchmarking Distance Functions in Siamese Networks for Current and Prior Mammogram Image Analysis.
Sahand Hamzehei, Afsana Ahsan Jeny, Annie Jin, Clifford Yang, Sheida Nabavi

Proceedings (IEEE Int Conf Bioinformatics Biomed)· December 2024

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Improved allele-specific single-cell copy number estimation in low-coverage DNA-sequencing.
Samson Weiner, Bingjun Li, Sheida Nabavi

Bioinformatics· August 2024

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Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms.
Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi

Comput Med Imaging Graph· April 2024

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A multimodal graph neural network framework for cancer molecular subtype classification.
Bingjun Li, Sheida Nabavi

BMC Bioinformatics· January 2024

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3D Biological/Biomedical Image Registration with enhanced Feature Extraction and Outlier Detection.
Sahand Hamzehei, Jun Bai, Gianna Raimondi, Rebecca Tripp, Linnaea Ostroff, Sheida Nabavi

ACM BCB· September 2023

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The Role of Deep Learning in Advancing Breast Cancer Detection Using Different Imaging Modalities: A Systematic Review.
Mohammad Madani, Mohammad Mahdi Behzadi, Sheida Nabavi

Cancers (Basel)· October 2022

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Feature fusion Siamese network for breast cancer detection comparing current and prior mammograms.
Jun Bai, Annie Jin, Tianyu Wang, Clifford Yang, Sheida Nabavi

Med Phys· June 2022

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Identification of Copy Number Alterations from Next-Generation Sequencing Data.
Sheida Nabavi, Fatima Zare

Adv Exp Med Biol· March 2022

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Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review.
Jun Bai, Russell Posner, Tianyu Wang, Clifford Yang, Sheida Nabavi

Med Image Anal· July 2021

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Single-cell classification using graph convolutional networks.
Tianyu Wang, Jun Bai, Sheida Nabavi

BMC Bioinformatics· July 2021

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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· April 2021

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Convolutional neural network for automated mass segmentation in mammography.
Dina Abdelhafiz, Jinbo Bi, Reda Ammar, Clifford Yang, Sheida Nabavi

BMC Bioinformatics· December 2020

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An immune-centric exploration of BRCA1 and BRCA2 germline mutation related breast and ovarian cancers.
Ewa Przybytkowski, Thomas Davis, Abdelrahman Hosny, Julia Eismann, Ursula A Matulonis, Sheida Nabavi

BMC Cancer· March 2020

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Transcriptome analysis reveals overlap in fusion genes in a phase I clinical cohort of TNBC and HGSOC patients treated with buparlisib and olaparib.
Julia Eismann, Yujing J Heng, Johannes M Waldschmidt, Ioannis S Vlachos, Kathryn P Gray, Sheida Nabavi

J Cancer Res Clin Oncol· February 2020

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A Unique Morphological Phenotype in Chemoresistant Triple-Negative Breast Cancer Reveals Metabolic Reprogramming and PLIN4 Expression as a Molecular Vulnerability.
Isabelle Sirois, Adriana Aguilar-Mahecha, Josiane Lafleur, Emma Fowler, Viet Vu, Sheida Nabavi

Mol Cancer Res· December 2019

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Copy Number Variation Detection Using Total Variation.
Fatima Zare, Sheida Nabavi

ACM BCB· September 2019

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Deep convolutional neural networks for mammography: advances, challenges and applications.
Dina Abdelhafiz, Clifford Yang, Reda Ammar, Sheida Nabavi

BMC Bioinformatics· June 2019

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Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data.
Tianyu Wang, Boyang Li, Craig E Nelson, Sheida Nabavi

BMC Bioinformatics· January 2019

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Noise cancellation using total variation for copy number variation detection.
Fatima Zare, Abdelrahman Hosny, Sheida Nabavi

BMC Bioinformatics· October 2018

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SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.
Tianyu Wang, Sheida Nabavi

Methods· August 2018

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Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?
Nancy Krieger, Sheida Nabavi, Pamela D Waterman, Ninah S Achacoso, Luana Acton

Cancer Causes Control· March 2018

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Differential gene expression analysis in single-cell RNA sequencing data.
Tianyu Wang, Sheida Nabavi

Proceedings (IEEE Int Conf Bioinformatics Biomed)· November 2017

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