Background Multimodal generative artificial intelligence (AI) technologies can produce preliminary radiology reports, and validation with reader studies is crucial for understanding the clinical value of these technologies. Purpose To assess the clin...
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...
Journal of the American College of Radiology : JACR
Mar 1, 2025
OBJECTIVE: Hepatocellular carcinoma (HCC) poses a heavy global disease burden; early diagnosis is critical to improve outcomes. Opportunistic screening-the use of imaging data acquired for other clinical indications for disease detection-as well as t...
OBJECTIVE: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for full-field digital mammography (FFDM) when applied to synthetic mammography (SM).
BACKGROUND: Borrmann type-4 (B-4) advanced gastric cancer is challenging to diagnose through routine endoscopy, leading to a poor prognosis. The objective of this study was to develop an artificial intelligence (AI)-based system capable of detecting ...
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...
Clinical and experimental dental research
Feb 1, 2025
OBJECTIVES: Given the complexity of temporomandibular joint disorders (TMDs) and their overlapping symptoms with other conditions, an accurate diagnosis necessitates a thorough examination, which can be time-consuming and resource-intensive. Conseque...
OBJECTIVES: This study aimed to assess the impact of a deep learning model on oral radiologists' ability to detect periapical radiolucencies on periapical radiographs. The secondary objective was to conduct a regression analysis to evaluate the effec...
OBJECTIVES: To investigate the impact of artificial intelligence (AI) on enhancing the sensitivity of digital mammograms in the detection and specification of grouped microcalcifications.
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