Rationale and Objectives Burnout, stemming from chronic work stress, is a significant issue
in the medical field, especially among radiologists. It leads to compromised patient care and …

Background Radiology practices have a high volume of unremarkable chest radiographs
and artificial intelligence (AI) could possibly improve workflow by providing an automatic …

Rationale and Objectives Burnout is a serious problem during medical residency and can
contribute to poorer resident and patient health. A thorough understanding of factors …

Artificial Intelligence (AI) applied to radiology is so vast that it provides applications ranging
from becoming a complete replacement for radiologists (a potential threat) to an efficient …

Objective To assess the impact of interruptions on radiologists' efficiency, accuracy, and job
satisfaction in interpreting screening mammograms. Methods This institutional review board …

This retrospective study evaluated a commercial deep learning (DL) software for chest
radiographs and explored its performance in different scenarios. A total of 477 patients (284 …

Compared with a previous study that used a dedicated AI tool for identifying “high-
confidence normal chest radiographs” in a subgroup of patients with posteroanterior chest …

Breast radiologists have high rates of burnout. Some contributing factors include the
sedentary nature of the occupation, reading room design and isolation associated with …

At our institution, a backlog of unread screening mammograms accumulated with a peak
turnaround time of 198 hours (8.25 days). Three major root causes of workflow inefficiencies …

Rationale and Objectives Given the immense time and energy radiologists dedicate to their
profession, the experience at work should be a major contributor to a meaningful and …