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N. Elshafeey · SciRah

Researcher profile · Semantic Scholar

N. Elshafeey

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N. Elshafeey — researcher profile on SciRah

h-index: 14
Works: 54
Citations: 691

Most-cited papers

Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma
N. Elshafeey, A. Kotrotsou, Ahmed Hassan, Nancy Elshafei +13 more
2019Nature Communications135 citations Open access
Semantic Scholar
A co-clinical radiogenomic validation study - Conserved magnetic resonance radiomic appearance of Periostin expressing Glioblastoma in patients and xenograft models
P. Zinn, S. Singh, A. Kotrotsou, I. Hassan +16 more
2018Clinical Cancer Research90 citations Open access
Semantic Scholar
MRI-based digital models forecast patient-specific treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer
Cheng-Yue Wu, Angela M. Jarrett, Zi-Jian Zhou, N. Elshafeey +14 more
2022Cancer Research67 citations Open access
Semantic Scholar
Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI
Zi-Jian Zhou, B. Adrada, R. Candelaria, N. Elshafeey +23 more
2023Scientific Reports46 citations Open access
Semantic Scholar
Radiomics analysis for predicting pembrolizumab response in patients with advanced rare cancers
R. Colen, C. Rolfo, M. Ak, M. Ayoub +14 more
2021Journal for ImmunoTherapy of Cancer42 citations Open access
Semantic Scholar
Dynamic contrast-enhanced MRI detects acute radiotherapy-induced alterations in mandibular microvasculature: prospective assessment of imaging biomarkers of normal tissue injury
V. Sandulache, B. Hobbs, R. A. S. Mohamed, S. Frank +21 more
2016Scientific Reports39 citations Open access
Semantic Scholar
A model combining pretreatment MRI radiomic features and tumor-infiltrating lymphocytes to predict response to neoadjuvant systemic therapy in triple-negative breast cancer.
J. E. Jimenez, Abeer H. Abdelhafez, E. Mittendorf, N. Elshafeey +15 more
2022European Journal of Radiology33 citations
Semantic Scholar
A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer.
K. Hwang, N. Elshafeey, A. Kotrotsou, Hui-Qin Chen +22 more
2023Radiology: Imaging Cancer29 citations Open access
Semantic Scholar
Pre-operative MRI radiomics model non-invasively predicts key genomic markers and survival in glioblastoma patients
M. Pease, Z. Gersey, M. Ak, A. Elakkad +8 more
2022Journal of Neuro-Oncology27 citations
Semantic Scholar
Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer
Benjamin C. Musall, Abeer H. Abdelhafez, B. Adrada, R. Candelaria +24 more
2021Journal of Magnetic Resonance Imaging27 citations Open access
Semantic Scholar
Assessment of Early Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer Using Amide Proton Transfer-weighted Chemical Exchange Saturation Transfer MRI: A Pilot Study.
Shu Zhang, G. Rauch, B. Adrada, M. Boge +14 more
2021Radiology: Imaging Cancer23 citations Open access
Semantic Scholar
Radiographic patterns of progression with associated outcomes after bevacizumab therapy in glioblastoma patients
D. Cachia, N. Elshafeey, C. Kamiya-Matsuoka, M. Hatami +4 more
2017Journal of Neuro-Oncology20 citations
Semantic Scholar
Clinical Outcomes in Non–Small-Cell Lung Cancer Patients Treated With EGFR-Tyrosine Kinase Inhibitors and Other Targeted Therapies Based on Tumor Versus Plasma Genomic Profiling
H. Tran, V. Lam, Y. Elamin, L. Hong +16 more
2021JCO Precision Oncology16 citations Open access
Semantic Scholar
Shedding Light on the 2016 World Health Organization Classification of Tumors of the Central Nervous System in the Era of Radiomics and Radiogenomics.
R. Colen, I. Hassan, N. Elshafeey, P. Zinn
2016Magnetic Resonance Imaging Clinics of North America15 citations
Semantic Scholar
Quantitative Apparent Diffusion Coefficients from Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer
Benjamin C. Musall, B. Adrada, R. Candelaria, Rania M. M. Mohamed +24 more
2022Journal of Magnetic Resonance Imaging14 citations Open access
Semantic Scholar
Radiomic analysis of pseudo-progression compared to true progression in glioblastoma patients: A large-scale multi-institutional study.
Srishti Abrol, A. Kotrotsou, Ahmed Hassan, N. Elshafeey +16 more
201712 citations
Semantic Scholar
Assessing the identifiability of model selection frameworks for the prediction of patient outcomes in the clinical breast cancer setting
Caleb M. Phillips, E. Lima, Cheng-Yue Wu, Angela M. Jarrett +5 more
2023Journal of Computer Science11 citations Open access
Semantic Scholar
Multicenter study to demonstrate radiomic texture features derived from MR perfusion images of pseudoprogression compared to true progression in glioblastoma patients.
N. Elshafeey, A. Kotrotsou, Dunia Giniebra Camejo, Srishti Abrol +9 more
201710 citations
Semantic Scholar
Radiomic signatures to predict response to targeted therapy and immune checkpoint blockade in melanoma patients (pts) on neoadjuvant therapy.
R. Colen, G. Ologun, P. Zinn, M. Ak +16 more
20206 citations
Semantic Scholar
100 Toward the Co-clinical Glioblastoma Treatment Paradigm—Radiomic Machine Learning Identifies Glioblastoma Gene Expression in Patients and Corresponding Xenograft Tumor Models
P. Zinn, S. Singh, A. Kotrotsou, I. Hassan +16 more
2018Neurosurgery5 citations
Semantic Scholar
Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs
Zi-Jian Zhou, B. Adrada, R. Candelaria, N. Elshafeey +23 more
2023Annual International Conference of the IEEE Engineering in Medicine and Biology Society3 citations Open access
Semantic Scholar
Author response to Cunha et al
R. Colen, C. Rolfo, M. Ak, M. Ayoub +14 more
2021Journal for ImmunoTherapy of Cancer2 citations Open access
Semantic Scholar
Radiomics to predict response to pembrolizumab in patients with advanced rare cancers.
R. Colen, Sara Ahmed, N. Elshafeey, D. Karp +11 more
20202 citations
Semantic Scholar
Abstract 3040: Radiomics discriminates pseudo-progression from true progression in glioblastoma patients: A large-scale multi-institutional study
Srishti Abrol, A. Kotrotsou, Ahmed Hassan, N. Elshafeey +24 more
2018Tumor Biology2 citations
Semantic Scholar
NIMG-28. INCREASED MUTATION BURDEN (HYPERMUTATION) IN GLIOMAS IS ASSOCIATED WITH A UNIQUE RADIOMIC TEXTURE SIGNATURE IN MAGNETIC RESONANCE IMAGING
I. Hassan, A. Kotrotsou, C. Matsuoka, Kristin D. Alfaro-Munoz +4 more
20172 citations Open access
Semantic Scholar
Abstract P6-01-06: Multi-Parametric MRI-Based Radiomics Models from Tumor and Peritumoral Regions as Potential Predictors of Treatment Response to Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer Patients
Rania M. M. Mohamed, B. Panthi, B. Adrada, R. Candelaria +35 more
2023Cancer Research1 citations
Semantic Scholar
Abstract PD11-06: Radiomics model based on magnetic resonance image compilation (MagIC) as early predictor of pathologic complete response to neoadjuvant systemic therapy in triple-negative breast cancer
N. Elshafeey, K. Hwang, B. Adrada, R. Candelaria +31 more
2022Cancer Research1 citations
Semantic Scholar
Abstract P3-03-06: Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response
M. Guirguis, B. Adrada, R. Candelaria, Jia Sun +25 more
2022Cancer Research1 citations
Semantic Scholar
Abstract PD6-06: Radiomic phenotypes from dynamic contrast-enhanced MRI (DCE-MRI) parametric maps for early prediction of response to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients
N. Elshafeey, B. Adrada, R. Candelaria, Abeer H. Abdelhafez +31 more
2021Poster Spotlight Session Abstracts1 citations
Semantic Scholar
P1.01-98 Outcomes in Advanced NSCLC Patients Treated with 1st Line EGFR-TKI Based on Mutation Detection from Tissue or cfDNA-Based Genomic Sequencing
H. Tran, V. Lam, M. Vasquez, L. Hong +15 more
2019Journal of Thoracic Oncology1 citations Open access
Semantic Scholar
213 Radiomic Machine Learning Algorithms Discriminate Pseudo-Progression From True Progression in Glioblastoma Patients: A Multi-Institutional Study
P. Zinn, Srishti Abrol, A. Kotrotsou, Ahmed Hassan +23 more
2018Neurosurgery1 citations
Semantic Scholar
A unique MRI-based radiomic signature predicts hypermutated glioma genotype.
I. Hassan, A. Kotrotsou, C. Kamiya-Matsuoka, Kristin D. Alfaro-Munoz +5 more
20181 citations
Semantic Scholar
P1.13-37 Clinical Evaluation of Plasma-Based (cfDNA) Genomic Profiling in Over 1,000 Patients with Advanced Non-Small Cell Lung Cancer
H. Tran, V. Lam, M. Vasquez, L. Hong +18 more
2018Journal of Thoracic Oncology1 citations Open access
Semantic Scholar
Interrogating machine learning classifiers and dimensionality reduction techniques for radiomic prediction of glioma tumor grade.
K. Wahid, A. Kotrotsou, Srishti Abrol, Ahmed Hassan +2 more
20181 citations
Semantic Scholar
NIMG-03. RADIOMIC TEXTURE ANALYSIS TO PREDICT RESPONSE TO IMMUNOTHERAPY
R. Colen, Ahmed Hassan, N. Elshafeey, P. Zinn +2 more
2018Neuro-Oncology1 citations Open access
Semantic Scholar
From K-space to Nucleotide: Insights Into the Radiogenomics of Brain Tumors
N. Elshafeey, I. Hassan, P. Zinn, R. Colen
2017Topics in Magnetic Resonance Imaging (TMRI)1 citations
Semantic Scholar
NIMG-91. RADIOMIC ANALYSIS OF PSEUDO-PROGRESSION COMPARED TO TRUE PROGRESSION IN GLIOBLASTOMA PATIENTS: A LARGE-SCALE MULTI-INSTITUTIONAL STUDY
Srishti Abrol, A. Kotrotsou, Ahmed Hassan, N. Elshafeey +21 more
20171 citations Open access
Semantic Scholar
NIMG-29. RADIOMIC ANALYSIS ON APPARENT DIFFUSION COEFFICIENT (ADC) MAPS PREDICTS PLATELET-DERIVED GROWTH FACTOR RECEPTOR ALPHA (PDGFRA) GENE AMPLIFICATION FOR NEWLY DIAGNOSED GLIOBLASTOMA PATIENTS
Stefania Maraka, A. Kotrotsou, Srishti Abrol, Ahmed Hassan +5 more
20171 citations Open access
Semantic Scholar
Abstract P6-01-34: Longitudinal DCE-MRI Radiomic Models for Early Prediction of Response to Neoadjuvant Systemic Therapy (NAST) in Triple Negative Breast Cancer (TNBC) Patients
B. Panthi, Rania M. M. Mohamed, B. Adrada, R. Candelaria +35 more
2023Cancer Research0 citations
Semantic Scholar
Abstract P6-01-35: A Pre-operative Dynamic Contrast Enhanced MRI-Based Radiomics Models as Predictors of Treatment Response after Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer Patients
Rania M. M. Mohamed, B. Panthi, B. Adrada, R. Candelaria +27 more
2023Cancer Research0 citations
Semantic Scholar
Abstract 2736: Forecasting treatment response to neoadjuvant therapy in triple-negative breast cancer via an image-guided digital twin
Cheng-Yue Wu, Angela M. Jarrett, Zi-Jian Zhou, N. Elshafeey +14 more
2022Cancer Research0 citations
Semantic Scholar
Abstract P3-02-03: Quantitative molecular breast imaging for early prediction of neoadjuvant systemic therapy response in locally advanced breast cancer patients
M. Patel, B. Adrada, B. Lopez, R. Candelaria +17 more
2022Cancer Research0 citations
Semantic Scholar
Abstract P1-08-03: Deep learning for early prediction of neoadjuvant chemotherapy response in triple negative breast cancers
Zi-Jian Zhou, N. Elshafeey, David E Rauch, B. Adrada +22 more
2022Cancer Research0 citations
Semantic Scholar
Abstract PD11-07: Integrated model for early prediction of neoadjuvant systemic therapy response in triple negative breast cancer
G. Rauch, R. Candelaria, M. Guirguis, M. Boge +25 more
2022Cancer Research0 citations
Semantic Scholar
Abstract P1-08-08: Forecasting treatment response to neoadjuvant systemic therapy in triple negative breast cancer viamathematical modeling and quantitative MRI
Cheng-Yue Wu, Angela M. Jarrett, Zi-Jian Zhou, N. Elshafeey +15 more
2022Cancer Research0 citations
Semantic Scholar
Abstract PS3-01: Quantitative dynamic contrast-enhanced (DCE) MRI radiomic phenotypes for prediction of nodal and distal metastasis in breast cancer patients
G. Rauch, K. Drukker, N. Elshafeey, Rania M. M. Mohamed +7 more
2021Poster Session Abstracts0 citations
Semantic Scholar
Abstract PD6-07: Volumetric changes on longitudinal dynamic contrast enhanced MR imaging (DCE-MRI) as an early treatment response predictor to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients
G. Rauch, Adrada E Beatriz, R. Candelaria, N. Elshafeey +29 more
2021Poster Spotlight Session Abstracts0 citations
Semantic Scholar
Abstract PS3-08: Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study
Shu Zhang, G. Rauch, B. Adrada, M. Boge +30 more
2021Poster Session Abstracts0 citations
Semantic Scholar
ANGI-16. EARLY DETECTION OF TUMOR CELL PROLIFERATION IS ASSOCIATED WITH A UNIQUE RADIOMIC BIOMARKER IN PRECLINICAL GLIOBLASTOMA XENOGRAFT AND PATIENTS
I. Hassan, S. Singh, J. Mosley, N. Elshafeey +4 more
2018Neuro-Oncology0 citations Open access
Semantic Scholar
Peer Review #1 of "Classification of the glioma grading using radiomics analysis (v0.2)"
Hwan-ho Cho, Seung-Hak Lee, Jonghoon Kim, Hyunjin Park +208 more
20180 citations Open access
Semantic Scholar

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