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Fangya Tan

Showing results (1-10 of 8) with videos related to

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Diagnostics (Basel, Switzerland)|June 26, 2026
Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall ResponseFangya Tan, Bowen Long
Bioengineering (Basel, Switzerland)|August 29, 2024
Deciphering Factors Contributing to Cost-Effective Medicine Using Machine LearningBowen Long, Jinfeng Zhou, Fangya Tan, et al.
Diagnostics (Basel, Switzerland)|March 14, 2026
A Unified Framework for Survival Prediction: Combining Machine Learning Feature Selection with Traditional Survival Analysis in Heart Failure and METABRIC Breast CancerFangya Tan, Jian-Guo Zhou, Shuqiao Li, et al.
Iscience|December 6, 2024
Efficacy of radiotherapy combined with atezolizumab or docetaxel in patients with previously treated NSCLCJunzhu Xu, Haitao Wang, Chi Zhang, et al.
Frontiers in Immunology|August 4, 2025
Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancerJuanyan Shen, Junliang Ma, Shaolin Chen, et al.
Frontiers in Immunology|July 18, 2022
Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning MethodsJian-Guo Zhou, Ada Hang-Heng Wong, Haitao Wang, et al.
BMJ Oncology|January 31, 2025
Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapyJian-Guo Zhou, Jie Yang, Haitao Wang, et al.
Frontiers in Immunology|September 19, 2022
Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trialsJian-Guo Zhou, Ada Hang-Heng Wong, Haitao Wang, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Diagnostics (Basel, Switzerland)|June 26, 2026
Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall ResponseFangya Tan, Bowen Long
Bioengineering (Basel, Switzerland)|August 29, 2024
Deciphering Factors Contributing to Cost-Effective Medicine Using Machine LearningBowen Long, Jinfeng Zhou, Fangya Tan, et al.
Diagnostics (Basel, Switzerland)|March 14, 2026
A Unified Framework for Survival Prediction: Combining Machine Learning Feature Selection with Traditional Survival Analysis in Heart Failure and METABRIC Breast CancerFangya Tan, Jian-Guo Zhou, Shuqiao Li, et al.
Iscience|December 6, 2024
Efficacy of radiotherapy combined with atezolizumab or docetaxel in patients with previously treated NSCLCJunzhu Xu, Haitao Wang, Chi Zhang, et al.
Frontiers in Immunology|August 4, 2025
Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancerJuanyan Shen, Junliang Ma, Shaolin Chen, et al.
Frontiers in Immunology|July 18, 2022
Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning MethodsJian-Guo Zhou, Ada Hang-Heng Wong, Haitao Wang, et al.
BMJ Oncology|January 31, 2025
Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapyJian-Guo Zhou, Jie Yang, Haitao Wang, et al.
Frontiers in Immunology|September 19, 2022
Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trialsJian-Guo Zhou, Ada Hang-Heng Wong, Haitao Wang, et al.
Pageof 1