DeepPrognosis: Preoperative prediction of pancreatic cancer survival and surgical margin via comprehensive understanding of dynamic contrast-enhanced CT imaging and tumor-vascular contact parsing

Deep learning for fully-automated prediction of overall survival in patients with oropharyngeal cancer using FDG PET imaging: an international retrospective study

(2021) Nai-Ming Cheng et al.   CLINICAL CANCER RESEARCH

Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

(2020) Ole-Johan Skrede et al.   LANCET

Pancreatic adenocarcinoma: quantitative CT features are correlated with fibrous stromal fraction and help predict outcome after resection

(2020) Xiaoli Cai et al.   EUROPEAN RADIOLOGY

Preoperative CT-based Deep Learning Model for Predicting Disease-Free Survival in Patients with Lung Adenocarcinomas

(2020) Hyungjin Kim et al.   RADIOLOGY

Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma

(2020) Aaron J. Grossberg et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients

(2020) Zhenyu Tang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Pancreatic cancer

(2020) Jonathan D Mizrahi et al.   LANCET

Deep learning-based survival prediction for multiple cancer types using histopathology images

(2020) Ellery Wulczyn et al.   PLoS One

Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks

(2020) Jiawen Yao et al.   MEDICAL IMAGE ANALYSIS

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

(2020) Fabian Isensee et al.   NATURE METHODS

Pancreatic Cancer Imaging: A New Look at an Old Problem

(2020) Linda C. Chu et al.   Current Problems in Diagnostic Radiology

Cancer statistics, 2019

(2019) Rebecca L. Siegel et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages

(2019) Dong Nie et al.   Scientific Reports

Impact of resection margin status on recurrence and survival in pancreatic cancer surgery

(2019) W. S. Tummers et al.   BRITISH JOURNAL OF SURGERY

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

(2019) Yiwen Xu et al.   CLINICAL CANCER RESEARCH

Preoperative CT Classification of the Resectability of Pancreatic Cancer: Interobserver Agreement

(2019) Ijin Joo et al.   RADIOLOGY

Radiomics in stratification of pancreatic cystic lesions: Machine learning in action

(2019) Vipin Dalal et al.   CANCER LETTERS

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data

(2019) Ling Zhang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Defining and Predicting Early Recurrence in 957 Patients With Resected Pancreatic Ductal Adenocarcinoma

(2018) Vincent P. Groot et al.   ANNALS OF SURGERY

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis

(2018) Marc A. Attiyeh et al.   ANNALS OF SURGICAL ONCOLOGY

Repeatability and reproducibility of radiomic features: A systematic review

(2018) Alberto Traverso et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Radiomic Biomarkers to Refine Risk Models for Distant Metastasis in HPV-related Oropharyngeal Carcinoma

(2018) Jennifer Yin Yee Kwan et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Predicting cancer outcomes from histology and genomics using convolutional networks

(2018) Pooya Mobadersany et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Tumor heterogeneity of pancreas head cancer assessed by CT texture analysis: association with survival outcomes after curative resection

(2018) Gabin Yun et al.   Scientific Reports

Pancreatic Cancer CT: Prediction of Resectability according to NCCN Criteria

(2018) Seung Baek Hong et al.   RADIOLOGY

Resectable pancreatic adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting pathology and patient outcomes

(2017) Christophe Cassinotto et al.   EUROPEAN JOURNAL OF RADIOLOGY

CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges

(2017) Meghan G. Lubner et al.   RADIOGRAPHICS

CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma – a quantitative analysis

(2017) Armin Eilaghi et al.   BMC MEDICAL IMAGING

DeepPap: Deep Convolutional Networks for Cervical Cell Classification

(2017) Ling Zhang et al.   IEEE Journal of Biomedical and Health Informatics

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

(2017) Spyridon Bakas et al.   Scientific Data

Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT

(2016) Zhoubing Xu et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer

(2016) Yan-qi Huang et al.   JOURNAL OF CLINICAL ONCOLOGY

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

Pancreatic Ductal Adenocarcinoma

(2012) Ioannis T. Konstantinidis et al.   ANNALS OF SURGERY

Visually Isoattenuating Pancreatic Adenocarcinoma at Dynamic-Enhanced CT: Frequency, Clinical and Pathologic Characteristics, and Diagnosis at Imaging Examinations

(2010) Jin Hee Kim et al.   RADIOLOGY