Aims: The purpose of this paper is to prospectively evaluate the performance of an artificial
intelligence (AI) system in diagnosing thyroid nodules and to assess its potential value in …

Interpreting chest X-rays is a complex task, and artificial intelligence algorithms for this
purpose are currently being developed. It is important to perform external validations of …

Objective: Chest X-rays are the most commonly performed diagnostic examinations. An
artificial intelligence (AI) system that evaluates the images fast and accurately help reducing …

Rationale and Objectives Research on implementation of artificial intelligence (AI) in
radiology workflows and its impact on reports remains scarce. In this study, we aim to assess …

MRI is the leading method of evaluation in traumatic shoulder pathologies ranging from soft
tissue or bone edema to rupture of tendons or ligaments and subtle fractures of bone. MRI …

Importance The efficient and accurate interpretation of radiologic images is paramount.
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …

Background: The chest radiograph (CXR) is the most frequently performed radiological
examination worldwide. The increasing volume of CXRs performed in hospitals causes …

Objectives Chest radiographs (CXRs) are commonly performed in emergency units (EUs),
but the interpretation requires radiology experience. We developed an artificial intelligence …

Aim To evaluate the suitability of a deep-learning (DL) algorithm for identifying normality as
a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an …

Background Widespread implementation of machine learning models in diagnostic imaging
is restricted by dearth of expertise and resources. General purpose automated machine …