Publications by authors named "Bikash Panthi"

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Forecasting Chemoradiation Response Midtreatment for High-Grade Gliomas Through Patient-Specific Biology-Based Modeling.
David A Hormuth, Maguy Farhat, Bikash Panthi, Holly Langshaw, Mihir D Shanker

Int J Radiat Oncol Biol Phys· December 2025

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A data assimilation framework for predicting the spatiotemporal response of high-grade gliomas to chemoradiation.
Hugo J M Miniere, David A Hormuth, Ernesto A B F Lima, Maguy Farhat, Bikash Panthi

BMC Cancer· July 2025

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Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation.
Khushi C Hiremath, Kenan Atakishi, Ernesto A B F Lima, Maguy Farhat, Bikash Panthi

Philos Trans A Math Phys Eng Sci· April 2025

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Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer.
Zhan Xu, Zijian Zhou, Jong Bum Son, Haonan Feng, Beatriz E Adrada, Bikash Panthi

Cancers (Basel)· March 2025

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Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy.
Benjamin C Musall, David E Rauch, Rania M M Mohamed, Bikash Panthi, Medine Boge

J Magn Reson Imaging· October 2024

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Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
Rania M Mohamed, Bikash Panthi, Beatriz E Adrada, Medine Boge, Rosalind P Candelaria

Sci Rep· July 2024

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Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer.
Zhan Xu, David E Rauch, Rania M Mohamed, Sanaz Pashapoor, Zijian Zhou, Bikash Panthi

Cancers (Basel)· October 2023

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Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
Bikash Panthi, Rania M Mohamed, Beatriz E Adrada, Medine Boge, Rosalind P Candelaria

Front Oncol· October 2023

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A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer.
Ken-Pin Hwang, Nabil A Elshafeey, Aikaterini Kotrotsou, Huiqin Chen, Jong Bum Son, Bikash Panthi

Radiol Imaging Cancer· July 2023

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Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs.
Zijian Zhou, Beatriz E Adrada, Rosalind P Candelaria, Nabil A Elshafeey, Medine Boge, Bikash Panthi

Annu Int Conf IEEE Eng Med Biol Soc· July 2023

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Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI.
Bikash Panthi, Beatriz E Adrada, Rosalind P Candelaria, Mary S Guirguis, Clinton Yam

Cancers (Basel)· February 2023

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Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.
Zijian Zhou, Beatriz E Adrada, Rosalind P Candelaria, Nabil A Elshafeey, Medine Boge, Bikash Panthi

Sci Rep· January 2023

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