most citedCombining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning to Predict Lymph Node Metastasis in Head and Neck Cancer

112 citations · 151 across the 4 of their papers we have counts for

collaborators

4 papers

physics.med-ph2022★ 26 cited

Towards reliable head and neck cancers locoregional recurrence prediction using delta-radiomics and learning with rejection option

Kai Wang, Michael Dohopolski, Qiongwen Zhang +2

A reliable locoregional recurrence (LRR) prediction model is important for the personalized management of head and neck cancers (HNC) patients. This work aims to develop a delta-ra…

physics.med-ph2018★ 112 cited

Combining Many-objective Radiomics and 3-dimensional Convolutional Neural Network through Evidential Reasoning to Predict Lymph Node Metastasis in Head and Neck Cancer

Liyuan Chen, Zhiguo Zhou, David Sher +5

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential for treatment optimizati…

physics.med-ph2018★ 1 cited

Multifactorial cancer treatment outcome prediction through multifaceted radiomics

Zhiguo Zhou, David Sher, Qiongwen Zhang +6

Accurately predicting the treatment outcome plays a greatly important role in tailoring and adapting a treatment planning in cancer therapy. Although the development of different m…

physics.med-ph2018★ 12 cited

Predicting Lymph Node Metastasis in Head and Neck Cancer by Combining Many-objective Radiomics and 3-dimensioal Convolutional Neural Network through Evidential Reasoning

Zhiguo Zhou, Liyuan Chen, David Sher +5

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential for treatment optimizati…