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Purpose: Enhancing the speed and efficiency of clinical trial recruitment is a key objective across international health systems. This study aimed to use artificial intelligence (AI) applied in the Victorian Cancer Registry (VCR), a population-based cancer registry, to assess (1) if VCR received all relevant pathology reports for three clinical trials, (2) AI accuracy in auto-extracting information from pathology reports for recruitment, and (3) the number of participants approached for trial enrollment using the AI approach compared with standard hospital-based recruitment.

Methods: To verify pathology report accessibility for VCR trial enrollment, reports from the laboratory were cross-referenced.

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Background: Femoroacetabular impingement (FAI) is a well-recognized cause of hip pain in adults. The hip-spine relationship between the femur, pelvis, and lumbosacral spine has garnered recent attention in hip arthroplasty. However, the hip-spine relationship has not been well described in patients with FAI.

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False-Negative Review from the Mammography Audit: Refining Breast Imaging Practice.

Radiographics

February 2025

From the Washington University School of Medicine, Mallinckrodt Institute of Radiology, 510 S Kingshighway Blvd, St. Louis, MO 63110.

Annual review of false-negative (FN) mammograms is a mandatory and critical component of the Mammography Quality Standards Act (MQSA) annual mammography audit. FN review can help hone reading skills and improve the ability to detect cancers at mammography. Subtle architectural distortion, asymmetries (seen only on one view), small lesions, lesions with probably benign appearance (circumscribed regular borders), isolated microcalcifications, and skin thickening are the most common mammographic findings when the malignancy is visible at retrospective review of FN mammograms.

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Importance: Recently, the US Food and Drug Administration gave premarketing approval to an algorithm based on its purported ability to identify individuals at genetic risk for opioid use disorder (OUD). However, the clinical utility of the candidate genetic variants included in the algorithm has not been independently demonstrated.

Objective: To assess the utility of 15 genetic variants from an algorithm intended to predict OUD risk.

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Identification of Naloxone in Emergency Medical Services Data Substantially Improves by Processing Unstructured Patient Care Narratives.

Prehosp Emerg Care

January 2025

Institute for Pharmaceutical Outcomes & Policy, Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Lexington KY 40508, USA.

Objectives: Structured data fields, including medication fields involving naloxone, are routinely used to identify opioid overdoses in emergency medical services (EMS) data; between January 2021 and March 2024, there were approximately 1.2 million instances of naloxone administration. in the United States.

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