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http://dx.doi.org/10.1177/22925503241288573 | DOI Listing |
Radiographics
October 2025
Division of Neuroradiology, Department of Diagnostic and Interventional Radiology, The Hospital for Sick Children, Toronto, Ontario, Canada.
Pediatric stroke is garnering increased attention due to its rising incidence and significant impact on affected children, families, and the health care system. Arterial ischemic stroke (AIS) is a major subtype of pediatric stroke and often results from arterial occlusion. Diagnosis and treatment of acute ischemic stroke in children pose unique challenges, primarily because of nonspecific symptoms, lack of pediatric-focused imaging protocols, distinct causes (compared with in adults), and the large number of stroke mimics.
View Article and Find Full Text PDFJ Pers Med
July 2025
Department of Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
Pharmacogenomics (PGx) has emerged as a powerful tool to personalize drug selection and dosing based on a patient's genetic profile. However, there are a range of challenges that impede uptake in current clinical practice. For example, clinicians often express frustration with commercially available PGx panel tests, which fail to consistently include all key actionable PGx genes (according to the Clinical Pharmacogenetics Implementation Consortium (CPIC), Food and Drug Administration (FDA) PGx guidelines, or The Dutch Pharmacogenetics Working Group (DPWG) guidelines) and instead are too long with clinically unimportant information (unvalidated genotypes).
View Article and Find Full Text PDFBone Joint J
June 2025
Faculty of Health and Life Science, University of Liverpool, Liverpool, UK.
The deployment of AI in medical imaging, particularly in areas such as fracture detection, represents a transformative advancement in orthopaedic care. AI-driven systems, leveraging deep-learning algorithms, promise to enhance diagnostic accuracy, reduce variability, and streamline workflows by analyzing radiograph images swiftly and accurately. Despite these potential benefits, the integration of AI into clinical settings faces substantial barriers, including slow adoption across health systems, technical challenges, and a major lag between technology development and clinical implementation.
View Article and Find Full Text PDFJ Comput Assist Tomogr
March 2025
Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL.
In the rapidly evolving landscape of medical education, artificial intelligence (AI) holds transformative potential. This manuscript explores the integration of large language models (LLMs) in Radiology education and training. These advanced AI tools, trained on vast data sets, excel in processing and generating human-like text, and have even demonstrated the ability to pass medical board exams.
View Article and Find Full Text PDFJAMA Intern Med
May 2025
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Importance: Kidney transplant (KT) is the optimal treatment for end-stage kidney disease (ESKD). The evaluation process for KT is lengthy, time-consuming, and burdensome, and racial and ethnic disparities persist.
Objective: To investigate the potential association of the Kidney Transplant Fast Track (KTFT) evaluation approach with the likelihood of waitlisting, KT, and associated disparities compared with standard care.