A Review of Explainable Deep Learning Cancer Detection Models in Medical Imaging

Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

(2021) Mahmoud Elsisi et al.   SENSORS

Deep Learning-Based Industry 4.0 and Internet of Things towards Effective Energy Management for Smart Buildings

(2021) Mahmoud Elsisi et al.   SENSORS

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

(2021) Mahmoud N. Ali et al.   SENSORS

Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data

(2020) Shi-hui Zhen et al.   Frontiers in Oncology

Implementation of model explainability for a basic brain tumor detection using convolutional neural networks on MRI slices

(2020) Paul Windisch et al.   NEURORADIOLOGY

Breast tumor segmentation in ultrasound images using contextual-information-aware deep adversarial learning framework

(2020) Vivek Kumar Singh et al.   EXPERT SYSTEMS WITH APPLICATIONS

Fully Automated Breast Density Segmentation and Classification Using Deep Learning

(2020) Nasibeh Saffari et al.   Diagnostics

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

(2020) Erico Tjoa et al.   IEEE Transactions on Neural Networks and Learning Systems

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

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

How far have we come? Artificial intelligence for chest radiograph interpretation

(2019) K. Kallianos et al.   CLINICAL RADIOLOGY

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features

(2019) Clinton J. Wang et al.   EUROPEAN RADIOLOGY

Lung Cancer Detection From CT Image Using Improved Profuse Clustering and Deep Learning Instantaneously Trained Neural Networks

(2019) P. Mohamed Shakeel et al.   MEASUREMENT

Causability and explainabilty of artificial intelligence in medicine

(2019) Andreas Holzinger et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

On the interpretability of machine learning-based model for predicting hypertension

(2019) Radwa Elshawi et al.   BMC Medical Informatics and Decision Making

A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop

(2019) Curtis P. Langlotz et al.   RADIOLOGY

Local Interpretable Model-Agnostic Explanations for Classification of Lymph Node Metastases

(2019) Iam Palatnik de Sousa et al.   SENSORS

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

(2019) Ramprasaath R. Selvaraju et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Illuminating Clues of Cancer Buried in Prostate MR Image: Deep Learning and Expert Approaches

(2019) Jun Akatsuka et al.   Biomolecules

Unboxing AI - Radiological Insights Into a Deep Neural Network for Lung Nodule Characterization

(2019) Vasantha Kumar Venugopal et al.   ACADEMIC RADIOLOGY

Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data

(2019) Jie Hao et al.   BMC Medical Genomics

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Computer-aided diagnosis of prostate cancer on magnetic resonance imaging using a convolutional neural network algorithm

(2018) Junichiro Ishioka et al.   BJU INTERNATIONAL

A Radiomics Approach with CNN for Shear-wave Elastography Breast Tumor Classification

(2018) Yongjin Zhou et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network

(2018) Zhiwei Wang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI

(2018) Yang Song et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Breast Mass Detection in Digital Mammogram Based on Gestalt Psychology

(2018) Hongyu Wang et al.   Journal of Healthcare Engineering

The mythos of model interpretability

(2018) Zachary C. Lipton   COMMUNICATIONS OF THE ACM

SD-CNN: a Shallow-Deep CNN for Improved Breast Cancer Diagnosis

(2018) Fei Gao et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation

(2018) Tsung-Chen Chiang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning using Deep Neural Nets

(2018) Ravi K. Samala et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Interpreting Deep Visual Representations via Network Dissection

(2018) Bolei Zhou et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records

(2018) Bum Chul Kwon et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

Development and Validation of Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs

(2018) Ju Gang Nam et al.   RADIOLOGY

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset

(2018) Richard Ha et al.   JOURNAL OF DIGITAL IMAGING

Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images

(2018) Wenyuan Li et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Deep Learning in Mammography

(2017) Anton S. Becker et al.   INVESTIGATIVE RADIOLOGY

Large scale deep learning for computer aided detection of mammographic lesions

(2017) Thijs Kooi et al.   MEDICAL IMAGE ANALYSIS

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI

(2017) Xin Yang et al.   MEDICAL IMAGE ANALYSIS

Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network

(2017) Thijs Kooi et al.   MEDICAL PHYSICS

Explaining nonlinear classification decisions with deep Taylor decomposition

(2017) Grégoire Montavon et al.   PATTERN RECOGNITION

A Multisite Survey Study of EMR Review Habits, Information Needs, and Display Preferences among Medical ICU Clinicians Evaluating New Patients

(2017) Rodrigo Cartin-Ceba et al.   Applied Clinical Informatics

Nuclear Architecture Analysis of Prostate Cancer via Convolutional Neural Networks

(2017) Jin Tae Kwak et al.   IEEE Access

Artificial intelligence in healthcare: past, present and future

(2017) Fei Jiang et al.   JOURNAL OF INVESTIGATIVE MEDICINE

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning

(2017) Xinggang Wang et al.   Scientific Reports

The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary

(2016) David N. Louis et al.   ACTA NEUROPATHOLOGICA

Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography

(2016) Ravi K. Samala et al.   MEDICAL PHYSICS

Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity

(2014) Samuel J Webb et al.   Journal of Cheminformatics

Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer

(2013) Maryellen L. Giger et al.   Annual Review of Biomedical Engineering