Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists

A survey on incorporating domain knowledge into deep learning for medical image analysis

(2021) Xiaozheng Xie et al.   MEDICAL IMAGE ANALYSIS

The Application of Deep Learning in Cancer Prognosis Prediction

(2020) Wan Zhu et al.   Cancers

Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network

(2020) Hojin Kim et al.   Scientific Reports

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

(2019) Shiwen Shen et al.   EXPERT SYSTEMS WITH APPLICATIONS

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

(2019) Zhi Huang et al.   Frontiers in Genetics

Adversarial attacks on medical machine learning

(2019) Samuel G. Finlayson et al.   SCIENCE

Combining Handcrafted Features with Latent Variables in Machine Learning for Prediction of Radiation‐Induced Lung Damage

(2019) Sunan Cui et al.   MEDICAL PHYSICS

MR-based treatment planning in radiation therapy using a deep learning approach

(2019) Fang Liu et al.   Journal of Applied Clinical Medical Physics

Deep learning based enhanced tumor segmentation approach for MR brain images

(2019) Mamta Mittal et al.   APPLIED SOFT COMPUTING

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

(2019) Yiwen Xu et al.   CLINICAL CANCER RESEARCH

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

(2019) Titus J. Brinker et al.   EUROPEAN JOURNAL OF CANCER

Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

(2019) Mohammad Hesam Hesamian et al.   JOURNAL OF DIGITAL IMAGING

Ensemble of Deep Convolutional Neural Networks for Classification of Early Barrett’s Neoplasia Using Volumetric Laser Endomicroscopy

(2019) Roger Fonollà et al.   Applied Sciences-Basel

Association Analysis of Deep Genomic Features Extracted by Denoising Autoencoders in Breast Cancer

(2019) Qian Liu et al.   Cancers

Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives

(2019) Krzysztof J. Geras et al.   RADIOLOGY

Key challenges for delivering clinical impact with artificial intelligence

(2019) Christopher J. Kelly et al.   BMC Medicine

Deep Learning to Improve Breast Cancer Detection on Screening Mammography

(2019) Li Shen et al.   Scientific Reports

Techniques for interpretable machine learning

(2019) Mengnan Du et al.   COMMUNICATIONS OF THE ACM

Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss

(2018) Qingsong Yang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation

(2018) Sérgio Pereira et al.   MEDICAL IMAGE ANALYSIS

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

DermaKNet: Incorporating the knowledge of dermatologists to Convolutional Neural Networks for skin lesion diagnosis

(2018) Ivan Gonzalez Diaz   IEEE Journal of Biomedical and Health Informatics

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

Interpretable and Expandable Deep Learning Diagnosis System for Multiple Ocular Diseases: Elaborately Simulating Doctors� working (Preprint)

(2018) Kai Zhang et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Clinically applicable deep learning for diagnosis and referral in retinal disease

(2018) Jeffrey De Fauw et al.   NATURE MEDICINE

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

(2018) Pranav Rajpurkar et al.   PLOS MEDICINE

Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network

(2017) Hu Chen et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

(2017) Babak Ehteshami Bejnordi et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Unintended Consequences of Machine Learning in Medicine

(2017) Federico Cabitza et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data

(2017) Fadhl M. Alakwaa et al.   JOURNAL OF PROTEOME RESEARCH

Brain tumor segmentation with Deep Neural Networks

(2017) Mohammad Havaei et al.   MEDICAL IMAGE ANALYSIS

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets

(2017) Natalia Antropova et al.   MEDICAL PHYSICS

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer

(2017) Paolo Inglese et al.   Chemical Science

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

(2017) Safoora Yousefi et al.   Scientific Reports

Deep Learning for Health Informatics

(2017) Daniele Ravi et al.   IEEE Journal of Biomedical and Health Informatics

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

(2017) Jiangwei Lao et al.   Scientific Reports

Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge

(2015) Katarzyna Tomczak et al.   Wspolczesna Onkologia-Contemporary Oncology

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

(2013) Kenneth Clark et al.   JOURNAL OF DIGITAL IMAGING