Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency...
Background Although artificial intelligence is actively being developed for prostate MRI, few studies have prospectively validated these tools. Purpose To compare the diagnostic performance of a commercial deep learning algorithm (DLA) and radiologis...
Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial planes) can calculate bone mineral density (BMD) and predict osteoporosis-related outcomes. Purpose...
European journal of pain (London, England)
Mar 1, 2025
BACKGROUND: Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop and validate a machine learning tool to predict the recurrence risk in patients with CLBP by using mu...
OBJECTIVES: To audit prospectively the accuracy, time saving, and utility of a commercial artificial intelligence auto-contouring tool (AIAC). To assess the reallocation of time released by AIAC.
Journal of cataract and refractive surgery
Mar 1, 2025
PURPOSE: To assess a new objective deep learning model cataract grading method based on swept-source optical coherence tomography (SS-OCT) scans provided by the Anterion.
BACKGROUND: Intravenous (IV) fluid contamination within clinical specimens causes an operational burden on the laboratory when detected, and potential patient harm when undetected. Even mild contamination is often sufficient to meaningfully alter res...
Liver international : official journal of the International Association for the Study of the Liver
Feb 1, 2025
BACKGROUND AND AIM: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoimmune hepatitis (AIH) is critical yet challenging. We aim to develop and validate a machine learning (ML)-based model to aid in this differentiation.
Journal of the American Medical Informatics Association : JAMIA
Feb 1, 2025
OBJECTIVE: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout.
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