85 citations · 159 across the 5 of their papers we have counts for
5 papers
Predicting the risk of pancreatic cancer with a CT-based ensemble AI algorithm
Chenjie Zhou MD, Jianhua Ma Ph. D, Xiaoping Xu MD +9
Objectives: Pancreatic cancer is a lethal disease, hard to diagnose and usually results in poor prognosis and high mortality. Developing an artificial intelligence (AI) algorithm t…
Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features
Shulong Li, Panpan Xu, Bin Li +8
To predict lung nodule malignancy with a high sensitivity and specificity, we propose a fusion algorithm that combines handcrafted features (HF) into the features learned at the ou…
Automatic multi-objective based feature selection for classification
Zhiguo Zhou, Shulong Li, Genggeng Qin +3
Objective: Accurately classifying the malignancy of lesions detected in a screening scan is critical for reducing false positives. Radiomics holds great potential to differentiate…
Constructing multi-modality and multi-classifier radiomics predictive models through reliable classifier fusion
Zhiguo Zhou, Zhi-Jie Zhou, Hongxia Hao +5
Radiomics aims to extract and analyze large numbers of quantitative features from medical images and is highly promising in staging, diagnosing, and predicting outcomes of cancer t…
Shell feature: a new radiomics descriptor for predicting distant failure after radiotherapy in non-small cell lung cancer and cervix cancer
Hongxia Hao, Zhiguo Zhou, Shulong Li +10
Purpose To develop and demonstrate a novel tumor shell feature for predicting distant failure in non-small cell lung cancer (NSCLC) and cervical cancer (CC) patients. Patients and…