Chest radiographs and machine learning – Past, present and future

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

(2020) Davide Chicco et al.   BMC GENOMICS

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study

(2020) Eui Jin Hwang et al.   EUROPEAN RADIOLOGY

Augmenting Interpretation of Chest Radiographs With Deep Learning Probability Maps

(2020) Brian Hurt et al.   JOURNAL OF THORACIC IMAGING

Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography

(2020) Xiaohua Wang et al.   OCCUPATIONAL AND ENVIRONMENTAL MEDICINE

Ethical thinking machines in surgery and the requirement for clinical leadership

(2020) Quinlan D. Buchlak et al.   AMERICAN JOURNAL OF SURGERY

Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs

(2020) Johannes Rueckel et al.   INVESTIGATIVE RADIOLOGY

A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study

(2020) Xiao-Ling Zou et al.   PLoS One

Deep Learning–based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs

(2020) Sowon Jang et al.   RADIOLOGY

Clinical Validation of a Deep Learning Algorithm for Detection of Pneumonia on Chest Radiographs in Emergency Department Patients with Acute Febrile Respiratory Illness

(2020) Jae Hyun Kim et al.   Journal of Clinical Medicine

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

(2020) Samantha Cruz Rivera et al.   BMJ-British Medical Journal

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents

(2020) Joy T. Wu et al.   JAMA Network Open

Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation

(2020) Ivo Baltruschat et al.   EUROPEAN RADIOLOGY

Causability and explainabilty of artificial intelligence in medicine

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

Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization

(2019) F. Pasa et al.   Scientific Reports

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks

(2019) Johnatan Carvalho Souza et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Exploring Large-scale Public Medical Image Datasets

(2019) Luke Oakden-Rayner   ACADEMIC RADIOLOGY

Deep Convolutional Neural Network–based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs

(2019) Yongsik Sim et al.   RADIOLOGY

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department

(2019) Eui Jin Hwang et al.   RADIOLOGY

Big Data and Machine Learning in Health Care

(2018) Andrew L. Beam et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Bias in Radiology: The How and Why of Misses and Misinterpretations

(2018) Lindsay P. Busby et al.   RADIOGRAPHICS

Visual interpretability for deep learning: a survey

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

Fundamentals of Diagnostic Error in Imaging

(2018) Jason N. Itri et al.   RADIOGRAPHICS

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

(2018) Pranav Rajpurkar et al.   PLOS MEDICINE

Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study

(2018) John R. Zech et al.   PLOS MEDICINE

Chest Radiographs in Congestive Heart Failure: Visualizing Neural Network Learning

(2018) Jarrel C. Y. Seah et al.   RADIOLOGY

The Seattle spine score: Predicting 30-day complication risk in adult spinal deformity surgery

(2017) Quinlan D. Buchlak et al.   JOURNAL OF CLINICAL NEUROSCIENCE

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks

(2017) Paras Lakhani et al.   RADIOLOGY

Missed lung cancer: when, where, and why?

(2017) Annemilia del Ciello et al.   Diagnostic and Interventional Radiology

Predicting the Future — Big Data, Machine Learning, and Clinical Medicine

(2016) Ziad Obermeyer et al.   NEW ENGLAND JOURNAL OF MEDICINE

Deep learning

(2015) Yann LeCun et al.   NATURE

Comparison of Dual-Energy Subtraction and Electronic Bone Suppression Combined With Computer-Aided Detection on Chest Radiographs: Effect on Human Observers' Performance in Nodule Detection

(2013) Zsolt Szucs-Farkas et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Lung Nodules: Improved Detection with Software That Suppresses the Rib and Clavicle on Chest Radiographs

(2011) Matthew Thomas Freedman et al.   RADIOLOGY

New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)

(2008) E.A. Eisenhauer et al.   EUROPEAN JOURNAL OF CANCER

Digital chest radiography: an update on modern technology, dose containment and control of image quality

(2008) Cornelia Schaefer-Prokop et al.   EUROPEAN RADIOLOGY