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Beiji Zou

Showing results (41-50 of 48) with videos related to

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Computer Methods and Programs in Biomedicine|March 6, 2024
Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI dataPeishan Dai, Yun Shi, Da Lu, et al.
Journal of Affective Disorders|July 19, 2023
Classification of recurrent major depressive disorder using a new time series feature extraction method through multisite rs-fMRI dataPeishan Dai, Da Lu, Yun Shi, et al.
Behavioural Brain Research|August 22, 2022
The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI dataPeishan Dai, Tong Xiong, Xiaoyan Zhou, et al.
Journal of Imaging Informatics in Medicine|March 22, 2024
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy RestrictionDaniel D Kim, Rajat S Chandra, Li Yang, et al.
Journal of Imaging Informatics in Medicine|April 8, 2024
An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate CancerYang Li, Maliha R Imami, Linmei Zhao, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|January 16, 2020
Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR ImagingIanto Lin Xi, Yijun Zhao, Robin Wang, et al.
Neuro-Oncology|June 26, 2021
Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumorsJian Peng, Daniel D Kim, Jay B Patel, et al.
Neuro-Oncology|September 22, 2021
Corrigendum to: Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumorsJian Peng, Daniel D Kim, Jay B Patel, et al.
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Showing results (41-50 of 48) with videos related to

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You have reached the last page of results.This site can display upto 48 results.
Computer Methods and Programs in Biomedicine|March 6, 2024
Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI dataPeishan Dai, Yun Shi, Da Lu, et al.
Journal of Affective Disorders|July 19, 2023
Classification of recurrent major depressive disorder using a new time series feature extraction method through multisite rs-fMRI dataPeishan Dai, Da Lu, Yun Shi, et al.
Behavioural Brain Research|August 22, 2022
The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI dataPeishan Dai, Tong Xiong, Xiaoyan Zhou, et al.
Journal of Imaging Informatics in Medicine|March 22, 2024
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy RestrictionDaniel D Kim, Rajat S Chandra, Li Yang, et al.
Journal of Imaging Informatics in Medicine|April 8, 2024
An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate CancerYang Li, Maliha R Imami, Linmei Zhao, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|January 16, 2020
Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR ImagingIanto Lin Xi, Yijun Zhao, Robin Wang, et al.
Neuro-Oncology|June 26, 2021
Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumorsJian Peng, Daniel D Kim, Jay B Patel, et al.
Neuro-Oncology|September 22, 2021
Corrigendum to: Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumorsJian Peng, Daniel D Kim, Jay B Patel, et al.
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