相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification
Ying Ren et al.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2020)
Machine Learning and Imaging Informatics in Oncology
Huan-Hsin Tseng et al.
ONCOLOGY (2020)
Machine learning helps identifying volume-confounding effects in radiomics
Alberto Traverso et al.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2020)
Radiomic Features at Contrast-enhanced CT Predict Recurrence in Early Stage Hepatocellular Carcinoma: A Multi-Institutional Study
Gu-Wei Ji et al.
RADIOLOGY (2020)
Radiogenomics predicts the expression of microRNA-1246 in the serum of esophageal cancer patients
Isamu Hoshino et al.
SCIENTIFIC REPORTS (2020)
Clinical characteristics and prognosis of 2887 patients with hepatocellular carcinoma A single center 14 years experience from China
Chun-yan Wang et al.
MEDICINE (2019)
CT-based peritumoral radiomics signatures to predict early recurrence in hepatocellular carcinoma after curative tumor resection or ablation
Quan-yuan Shan et al.
CANCER IMAGING (2019)
Comparing various scoring system for predicting overall survival according to treatment modalities in hepatocellular carcinoma focused on platelet-albumin-bilirubin (PALBI) and albumin-bilirubin (ALBI) grade: A nationwide cohort study
Soon Kyu Lee et al.
PLOS ONE (2019)
Radiomics analysis enables recurrence prediction for hepatocellular carcinoma after liver transplantation
Donghui Guo et al.
EUROPEAN JOURNAL OF RADIOLOGY (2019)
Platelets and Hepatocellular Cancer: Bridging the Bench to the Clinics
Quirino Lai et al.
CANCERS (2019)
Machine learning for radiomics-based multimodality and multiparametric modeling
Lise Wei et al.
QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2019)
Resource Efficient 3D Convolutional Neural Networks
Okan Koepueklue et al.
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW) (2019)
Imaging-Genomic Study of Head and Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes and Genomic Mechanisms via Integration of The Cancer Genome Atlas and The Cancer Imaging Archive
Yitan Zhu et al.
JCO CLINICAL CANCER INFORMATICS (2019)
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network
Jared L. Katzman et al.
BMC MEDICAL RESEARCH METHODOLOGY (2018)
Investigating multi-radiomic models for enhancing prediction power of cervical cancer treatment outcomes
Baderaldeen A. Altazi et al.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2018)
Radiomics in radiooncology - Challenging the medical physicist
Jan C. Peeken et al.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2018)
Predicting cancer outcomes from histology and genomics using convolutional networks
Pooya Mobadersany et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)
Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma: Current Trends and Controversies
Stephanie K. Schaub et al.
TECHNOLOGY IN CANCER RESEARCH & TREATMENT (2018)
A radiomics nomogram for preoperatively predicting prognosis of patients in hepatocellular carcinoma
Jie Peng et al.
TRANSLATIONAL CANCER RESEARCH (2018)
Modeling of Locoregional Control in Hepatocellular Carcinoma after Stereotactic Body Radiation Therapy by Integrating Clinical and Immune Cell Profiles
I. El Naqa et al.
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2018)
Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer
Kumardeep Chaudharyl et al.
CLINICAL CANCER RESEARCH (2018)
Albumin-Bilirubin and Platelet-Albumin-Bilirubin Grades Accurately Predict Overall Survival in High-Risk Patients Undergoing Conventional Transarterial Chemoembolization for Hepatocellular Carcinoma
Jan Hansmann et al.
JOURNAL OF VASCULAR AND INTERVENTIONAL RADIOLOGY (2017)
A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets
Natalia Antropova et al.
MEDICAL PHYSICS (2017)
Hepatocellular Carcinoma: Nomograms Based on the Albumin-Bilirubin Grade to Assess the Outcomes of Radiofrequency Ablation
Wei-Yu Kao et al.
RADIOLOGY (2017)
CT-based radiomics signature: a potential biomarker for preoperative prediction of early recurrence in hepatocellular carcinoma
Ying Zhou et al.
ABDOMINAL RADIOLOGY (2017)
Impact of hepatocellular carcinoma heterogeneity on computed tomography as a prognostic indicator
Shigeru Kiryu et al.
SCIENTIFIC REPORTS (2017)
Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study
Shaimaa Bakr et al.
JOURNAL OF MEDICAL IMAGING (2017)
Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy
Luca Cozzi et al.
BMC CANCER (2017)
Outcomes After Stereotactic Body Radiotherapy or Radiofrequency Ablation for Hepatocellular Carcinoma
Daniel R. Wahl et al.
JOURNAL OF CLINICAL ONCOLOGY (2016)
Radiomics: Images Are More than Pictures, They Are Data
Robert J. Gillies et al.
RADIOLOGY (2016)
A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities
M. Vallieres et al.
PHYSICS IN MEDICINE AND BIOLOGY (2015)
Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma
Yitan Zhu et al.
SCIENTIFIC REPORTS (2015)
Hepatocellular carcinoma review: Current treatment, and evidence-based medicine
Ali Raza et al.
WORLD JOURNAL OF GASTROENTEROLOGY (2014)
Long-term effect of stereotactic body radiation therapy for primary hepatocellular carcinoma ineligible for local ablation therapy or surgical resection. Stereotactic radiotherapy for liver cancer
Jung Hyun Kwon et al.
BMC CANCER (2010)
Cancer statistics, 2008
Ahmedin Jemal et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2008)
The MELD-Na is an independent short- and long-term prognostic predictor for hepatocellular carcinoma: A prospective survey
T. I. Huo et al.
DIGESTIVE AND LIVER DISEASE (2008)
Evidence-based incorporation of serum sodium concentration into MELD
Scott W. Biggins et al.
GASTROENTEROLOGY (2006)
Gene selection for cancer classification using support vector machines
I Guyon et al.
MACHINE LEARNING (2002)