Diagnostic Radiology

Radiomics and Machine Learning in Oral Healthcare.

The increasing storage of information, data, and forms of knowledge has led to the development of ne...

Deep learning-based segmentation of breast masses in dedicated breast CT imaging: Radiomic feature stability between radiologists and artificial intelligence.

A deep learning (DL) network for 2D-based breast mass segmentation in unenhanced dedicated breast CT...

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study.

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological ch...

Endoscopic diagnosis and treatment planning for colorectal polyps using a deep-learning model.

We aimed to develop a computer-aided diagnostic system (CAD) for predicting colorectal polyp histolo...

Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods.

Prostate cancer represents today the most typical example of a pathology whose diagnosis requires mu...

An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection.

The identification of lesion within medical image data is necessary for diagnosis, treatment and pro...

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

OBJECTIVE: To examine the association between the medical imaging utilization and information relate...

Survey on deep learning for pulmonary medical imaging.

As a promising method in artificial intelligence, deep learning has been proven successful in severa...

Artificial intelligence in medical imaging.

The medical specialty radiology has experienced a number of extremely important and influential tech...

Artificial intelligence in diagnostic imaging: impact on the radiography profession.

The arrival of artificially intelligent systems into the domain of medical imaging has focused atten...

Deep learning: definition and perspectives for thoracic imaging.

Relevance and penetration of machine learning in clinical practice is a recent phenomenon with multi...

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging res...

Machine Learning in Medical Imaging: All Journeys Begin With a Single Step.

Preparing for Artificial Intelligence: Systems-Level Implications for the Medical Imaging and Radiation Therapy Professions.

Innovations in artificial intelligence (AI) are driving a new industrial revolution, and as a result...

The Importance of Imaging Informatics and Informaticists in the Implementation of AI.

Imaging informatics is critical to the success of AI implementation in radiology. An imaging informa...

Decentralized distribution-sampled classification models with application to brain imaging.

BACKGROUND: In this age of big data, certain models require very large data stores in order to be in...

The Current State of Artificial Intelligence in Medical Imaging and Nuclear Medicine.

The last decade has seen a huge surge in interest surrounding artificial intelligence (AI). AI has b...

Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging.

Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understan...

Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study.

BACKGROUND: Upper gastrointestinal cancers (including oesophageal cancer and gastric cancer) are the...

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement.

This is a condensed summary of an international multisociety statement on ethics of artificial intel...

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement.

This is a condensed summary of an international multisociety statement on ethics of artificial intel...