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A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas

Neuro-oncology advances, 2020-12, Vol.2 (Supplement_4), p.iv42-iv48

2020

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Up-regulation of cerebral cytochrome-c-oxidase and hemodynamics by transcranial infrared laser stimulation: A broadband near-infrared spectroscopy study

Journal of cerebral blood flow and metabolism, 2017-12, Vol.37 (12), p.3789-3802

2017

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A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Neuro-oncology (Charlottesville, Va.), 2020-03, Vol.22 (3), p.402-411

2020

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Impact of heat on metabolic and hemodynamic changes in transcranial infrared laser stimulation measured by broadband near-infrared spectroscopy

Neurophotonics (Print), 2018-01, Vol.5 (1), p.011004-011004

2018

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Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition

American journal of neuroradiology : AJNR, 2024-09, Vol.45 (9), p.1276-1283

2024

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A Fully Automated Deep Learning Network for Brain Tumor Segmentation

Tomography (Ann Arbor), 2020-06, Vol.6 (2), p.186-193

2020

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Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Neuro-oncology (Charlottesville, Va.), 2020-03, Vol.22 (3), p.402-411

2020

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Errata: Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction

Journal of medical imaging (Bellingham, Wash.), 2023-01, Vol.10 (1), p.019801-019801

2023

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Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction

Journal of medical imaging (Bellingham, Wash.), 2022-01, Vol.9 (1), p.016001-016001

2022

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A Radiomic Machine Learning Model to Predict Treatment Response to Methotrexate and Survival Outcomes in Primary Central Nervous System Lymphoma (PCNSL)

Blood, 2020-11, Vol.136 (Supplement 1), p.29-30

2020

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Disparity Autoencoders for Multi-class Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.116-124

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Corrigendum to: A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas

Neuro-oncology advances, 2023-01, Vol.5 (1), p.vdac187-vdac187

2023

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Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas Using Deep Learning and MRI

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.99-112

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Simultaneous brain tumor segmentation and molecular profiling using deep learning and T2w magnetic resonance images

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques, 2021

Chaki, Jyotismita

2021

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Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning

American journal of neuroradiology : AJNR, 2024-03, Vol.45 (3), p.312-319

2024

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Federated benchmarking of medical artificial intelligence with MedPerf

Nature machine intelligence, 2023-07, Vol.5 (7), p.799-810

2023

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Invited: Automated Code generation for Information Technology Tasks in YAML through Large Language Models

2023 60th ACM/IEEE Design Automation Conference (DAC), 2023, p.1-4

2023

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BrainNET: Inference of Brain Network Topology Using Machine Learning

Brain connectivity, 2020-10, Vol.10 (8), p.422-435

2020

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Federated Learning for Brain Tumor Segmentation Using MRI and Transformers

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.444-454

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Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning

Journal of medical imaging (Bellingham, Wash.), 2019-10, Vol.6 (4), p.046003-046003

2019

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Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.448-457

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Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.148-157

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QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results

Machine Learning for Biomedical Imaging, 2022-08, Vol.1 (August 2022), p.1-54

2022

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A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas

Up-regulation of cerebral cytochrome-c-oxidase and hemodynamics by transcranial infrared laser stimulation: A broadband near-infrared spectroscopy study

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Impact of heat on metabolic and hemodynamic changes in transcranial infrared laser stimulation measured by broadband near-infrared spectroscopy

Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition

A Fully Automated Deep Learning Network for Brain Tumor Segmentation

Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Errata: Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction

Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction

A Radiomic Machine Learning Model to Predict Treatment Response to Methotrexate and Survival Outcomes in Primary Central Nervous System Lymphoma (PCNSL)

Disparity Autoencoders for Multi-class Brain Tumor Segmentation

Corrigendum to: A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas

Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas Using Deep Learning and MRI

Simultaneous brain tumor segmentation and molecular profiling using deep learning and T2w magnetic resonance images

Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning

Federated benchmarking of medical artificial intelligence with MedPerf

Invited: Automated Code generation for Information Technology Tasks in YAML through Large Language Models

BrainNET: Inference of Brain Network Topology Using Machine Learning

Federated Learning for Brain Tumor Segmentation Using MRI and Transformers

Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning

Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results

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