Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy

(2018) Anastasia Oikonomou et al.   Scientific Reports

Visual interpretability for deep learning: a survey

(2018) Quan-shi Zhang et al.   Frontiers of Information Technology & Electronic Engineering

Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data

(2017) Daniel Forsberg et al.   JOURNAL OF DIGITAL IMAGING

Large scale deep learning for computer aided detection of mammographic lesions

(2017) Thijs Kooi et al.   MEDICAL IMAGE ANALYSIS

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Radiomics: the bridge between medical imaging and personalized medicine

(2017) Philippe Lambin et al.   Nature Reviews Clinical Oncology

Quicksilver: Fast predictive image registration – A deep learning approach

(2017) Xiao Yang et al.   NEUROIMAGE

Integrated Diagnostics: The Computational Revolution Catalyzing Cross-disciplinary Practices in Radiology, Pathology, and Genomics

(2017) Claes F. Lundström et al.   RADIOLOGY

Defining the biological basis of radiomic phenotypes in lung cancer

(2017) Patrick Grossmann et al.   eLife

Is tumor location an independent prognostic factor in locally advanced non-small cell lung cancer treated with trimodality therapy?

(2017) Kazuhiko Shien et al.   Journal of Thoracic Disease

Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin

(2017) Mohsen Ghafoorian et al.   NeuroImage-Clinical

The prognostic value of CT radiomic features for patients with pulmonary adenocarcinoma treated with EGFR tyrosine kinase inhibitors

(2017) Hyungjin Kim et al.   PLoS One

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

(2017) Angel Cruz-Roa et al.   Scientific Reports

A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme

(2017) Jiangwei Lao et al.   Scientific Reports

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

(2017) Mohsen Ghafoorian et al.   Scientific Reports

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

(2017) Xiangxue Wang et al.   Scientific Reports

Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma

(2016) Patrick Grossmann et al.   BMC CANCER

Imaging genomics in cancer research: limitations and promises

(2016) Harrison X Bai et al.   BRITISH JOURNAL OF RADIOLOGY

A CNN Regression Approach for Real-Time 2D/3D Registration

(2016) Shun Miao et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

(2016) Varun Gulshan et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Radiomic phenotype features predict pathological response in non-small cell lung cancer

(2016) Thibaud P. Coroller et al.   RADIOTHERAPY AND ONCOLOGY

CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer

(2016) Elizabeth Huynh et al.   RADIOTHERAPY AND ONCOLOGY

Predictive and Prognostic Biomarkers in Non-Small Cell Lung Cancer

(2016) Shirish Gadgeel et al.   SEMINARS IN RESPIRATORY AND CRITICAL CARE MEDICINE

Global cancer statistics, 2012

(2015) Lindsey A. Torre et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Characterization of Conserved Toxicogenomic Responses in Chemically Exposed Hepatocytes across Species and Platforms

(2015) Nehme El-Hachem et al.   ENVIRONMENTAL HEALTH PERSPECTIVES

Recurrence Risk Factors Analysis for Stage I Non-small Cell Lung Cancer

(2015) Ching-Feng Wu et al.   MEDICINE

CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

(2015) Thibaud P. Coroller et al.   RADIOTHERAPY AND ONCOLOGY

Building Predictive Models inRUsing thecaretPackage

(2015) Max Kuhn   Journal of Statistical Software

Machine Learning methods for Quantitative Radiomic Biomarkers

(2015) Chintan Parmar et al.   Scientific Reports

Biomarkers in Early-Stage Non–Small-Cell Lung Cancer: Current Concepts and Future Directions

(2014) Mauricio Burotto et al.   Journal of Thoracic Oncology

A prospective study comparing the predictions of doctors versus models for treatment outcome of lung cancer patients: A step toward individualized care and shared decision making

(2014) Cary Oberije et al.   RADIOTHERAPY AND ONCOLOGY

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

mRMRe: an R package for parallelized mRMR ensemble feature selection

(2013) Nicolas De Jay et al.   BIOINFORMATICS

The causes and consequences of genetic heterogeneity in cancer evolution

(2013) Rebecca A. Burrell et al.   NATURE

Prediction of 2 years-survival in patients with stage I and II non-small cell lung cancer utilizing 18F-FDG PET/CT SUV quantifica

(2013) Angelina Cistaro et al.   Radiology and Oncology

Radiomics: Extracting more information from medical images using advanced feature analysis

(2012) Philippe Lambin et al.   EUROPEAN JOURNAL OF CANCER

Non-Small Cell Lung Cancer: Epidemiology, Risk Factors, Treatment, and Survivorship

(2012) Julian R. Molina et al.   MAYO CLINIC PROCEEDINGS

Non–Small Cell Lung Cancer: Histopathologic Correlates for Texture Parameters at CT

(2012) Balaji Ganeshan et al.   RADIOLOGY

survcomp: an R/Bioconductor package for performance assessment and comparison of survival models

(2011) Markus S. Schröder et al.   BIOINFORMATICS

Molecular signatures database (MSigDB) 3.0

(2011) A. Liberzon et al.   BIOINFORMATICS

Variability of Lung Tumor Measurements on Repeat Computed Tomography Scans Taken Within 15 Minutes

(2011) Geoffrey R. Oxnard et al.   JOURNAL OF CLINICAL ONCOLOGY

How Well Does the New Lung Cancer Staging System Predict for Local/Regional Recurrence After Surgery?: A Comparison of the TNM 6 and 7 Systems

(2011) Joseph M. Pepek et al.   Journal of Thoracic Oncology

Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

(2011) Balaji Ganeshan et al.   CANCER IMAGING

Tumors as Organs: Complex Tissues that Interface with the Entire Organism

(2010) Mikala Egeblad et al.   DEVELOPMENTAL CELL

The Impact of Additional Prognostic Factors on Survival and their Relationship with the Anatomical Extent of Disease Expressed by the 6th Edition of the TNM Classification of Malignant Tumors and the Proposals for the 7th Edition

(2010) Jean-Paul Sculier et al.   Journal of Thoracic Oncology

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Long-Term Results of the International Adjuvant Lung Cancer Trial Evaluating Adjuvant Cisplatin-Based Chemotherapy in Resected Lung Cancer

(2009) Rodrigo Arriagada et al.   JOURNAL OF CLINICAL ONCOLOGY

Evaluating Variability in Tumor Measurements from Same-day Repeat CT Scans of Patients with Non–Small Cell Lung Cancer

(2009) Binsheng Zhao et al.   RADIOLOGY