Yongju Yi
Guangzhou, China
Last Updated: 09/26/2026
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Found 9 publications
A pelvis MR transformer-based deep learning model for predicting lung metastases risk in patients with rectal cancer.
Journal: Frontiers in oncology
Published: September 15, 2024
Dynamic contrast-enhanced and diffusion-weighted MRI of cervical carcinoma: Correlations with Ki-67 proliferation status.
Journal: Magnetic resonance imaging
Published: May 09, 2024
Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?
Journal: Gastroenterology report
Published: November 01, 2023
A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas.
Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published: April 20, 2023
Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
Journal: European radiology
Published: November 21, 2021
Predicting treatment response from longitudinal images using multi-task deep learning.
Journal: Nature communications
Published: September 28, 2020
Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer.
Journal: Frontiers in oncology
Published: October 28, 2019
Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer.
Journal: Annals of surgical oncology
Published: November 19, 2018
Showing 1-9 of 9
Last Updated: 09/26/2026