Professor | Ning Zhenyuan | Asia Growth Partners

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Name	Ning Zhenyuan
Contact Information	jonnyning@foxmail.com
Language ability	English, Chinese
Province	Guangdong

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Name

Ning Zhenyuan

Contact Information

jonnyning@foxmail.com

Language ability

English, Chinese

Province

Guangdong

University/Lab Affiliation and Title	Southern Medical University
Faculty	Biomedical Engineering
Academic Background & Achievements	2014.09-2018.06 Bachelor: Southern Medical University, Biomedical Engineering 2019.11-2020.07 Visiting Scholar: University of North Carolina at Chapel Hill 2018.09-2023.06 Doctorate: Southern Medical University, Biomedical Engineering
Work Experience	2023.09-present - Southern Medical University - Associate Professor
Awards	ICMA Fellowship Award

University/Lab Affiliation and Title

Southern Medical University

Faculty

Biomedical Engineering

Academic Background & Achievements

2014.09-2018.06 Bachelor: Southern Medical University, Biomedical Engineering
2019.11-2020.07 Visiting Scholar: University of North Carolina at Chapel Hill
2018.09-2023.06 Doctorate: Southern Medical University, Biomedical Engineering

Work Experience

2023.09-present - Southern Medical University - Associate Professor

Awards

ICMA Fellowship Award

Areas of Focus	Medical image analysis and survival analysis
Publications	Mutual-assistance Learning for Standalone Mono-modality Survival Analysis of Human Cancers, Ning Z, et al., 2023 Multi-constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data, Ning Z, et al., 2023 Deep Cross-view Co-regularized Representation Learning for Glioma Subtype Identification, Ning Z, et al., 2021 Relation-induced Multi-modal Shared Representation Learning for Alzheimer’s Disease Diagnosis, Ning Z#, Xiao Q#, et al., 2021 SMU-Net: Saliency-guided Morphology-aware U-Net for Breast Lesion Segmentation in Ultrasound Image, Ning Z#, Zhong S#, et al., 2022 Relation-aware Shared Representation Learning for Cancer Prognosis Analysis with Auxiliary Clinical Variables and Incomplete Multi-modality Data, Ning Z#, Du D#, et al., 2022 Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features, Ning Z, et al., 2019 Adaptive Risk-aware Sharable and Individual Subspace Learning for Cancer Survival Analysis with Multi-modality Data, Zhao Z, Feng Q, Zhang Y, Ning Z., 2023 Integrative Analysis of Cross-modal Features for the Prognosis Prediction of Clear Cell Renal Cell Carcinoma, Ning Z#, Pan W#, et al., 2020 Dual-curriculum Contrastive Multi-instance Learning for Cancer Prognosis Analysis with Whole Slide Images, Tu C, Zhang Y, Ning, Z., 2022 Deep Convolutional Neural Network-aided Detection of Portal Hypertension in Patients with Cirrhosis, Liu Y#, Ning Z#, Örmeci N#, et al., 2020 Development and Validation of a Radiomics Signature for Clinically Significant Portal Hypertension in Cirrhosis (CHESS1701): A Prospective Multicenter Study, Liu F#, Ning Z#, Liu Y#, et al., 2018 Multi-scale Gradational-order Fusion Framework for Breast Lesions Classification using Ultrasound Images, Ning Z, et al., 2020 LDGAN: Longitudinal-diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI, Ning Z, et al., 2020

Areas of Focus

Medical image analysis and survival analysis

Publications

Mutual-assistance Learning for Standalone Mono-modality Survival Analysis of Human Cancers, Ning Z, et al., 2023
Multi-constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data, Ning Z, et al., 2023
Deep Cross-view Co-regularized Representation Learning for Glioma Subtype Identification, Ning Z, et al., 2021
Relation-induced Multi-modal Shared Representation Learning for Alzheimer’s Disease Diagnosis, Ning Z#, Xiao Q#, et al., 2021
SMU-Net: Saliency-guided Morphology-aware U-Net for Breast Lesion Segmentation in Ultrasound Image, Ning Z#, Zhong S#, et al., 2022
Relation-aware Shared Representation Learning for Cancer Prognosis Analysis with Auxiliary Clinical Variables and Incomplete Multi-modality Data, Ning Z#, Du D#, et al., 2022
Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features, Ning Z, et al., 2019
Adaptive Risk-aware Sharable and Individual Subspace Learning for Cancer Survival Analysis with Multi-modality Data, Zhao Z, Feng Q, Zhang Y*, Ning Z*., 2023
Integrative Analysis of Cross-modal Features for the Prognosis Prediction of Clear Cell Renal Cell Carcinoma, Ning Z#, Pan W#, et al., 2020
Dual-curriculum Contrastive Multi-instance Learning for Cancer Prognosis Analysis with Whole Slide Images, Tu C, Zhang Y*, Ning, Z*., 2022
Deep Convolutional Neural Network-aided Detection of Portal Hypertension in Patients with Cirrhosis, Liu Y#, Ning Z#, Örmeci N#, et al., 2020
Development and Validation of a Radiomics Signature for Clinically Significant Portal Hypertension in Cirrhosis (CHESS1701): A Prospective Multicenter Study, Liu F#, Ning Z#, Liu Y#, et al., 2018
Multi-scale Gradational-order Fusion Framework for Breast Lesions Classification using Ultrasound Images, Ning Z, et al., 2020
LDGAN: Longitudinal-diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI, Ning Z, et al., 2020

Cancer Prognosis Brain Diseases Ultrasound Intelligent Algorithms Clinical Applications Image Analysis Survival Analysis Diagnosis Medical Imaging Biomedical Engineering

Jingfeng Bai - Shanghai Jiao Tong University

Yazhu Chen - Shanghai Jiao Tong University

Zhou Chen - Shanghai Jiao Tong University

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