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Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its growing rise with hesitancy or outright skepticism. However, AI is becoming increasingly pervasive in our society, from algorithms helping to sift through airline fares to substituting words in emails and SMS text messages based on user choices. Data collection is ongoing and is being leveraged by software platforms to analyze patterns and make predictions across multiple industries. Health care is gradually becoming part of this technological transformation, as advancements in computational power and storage converge with the rapid expansion of digitized medical information. Given the growing and inevitable integration of AI into health care systems, it is our viewpoint that pediatricians urgently require training and orientation to the uses, promises, and pitfalls of AI in medicine. AI is unlikely to solve the full array of complex challenges confronting pediatricians today; however, if used responsibly, it holds great potential to improve many aspects of care for providers, children, and families. Our aim in this viewpoint is to provide clinicians with a targeted introduction to the field of AI in pediatrics, including key promises, pitfalls, and clinical applications, so they can play a more active role in shaping the future impact of AI in medicine.
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http://dx.doi.org/10.2196/49022 | DOI Listing |
Ann Diagn Pathol
September 2025
Associate Professor of Anatomic Pathology, Faculty of Medicine, Ain Shams University, Cairo, Egypt. Electronic address:
World J Surg
September 2025
Department of Ethics, Law and Humanities, Amsterdam UMC (Location AMC), University of Amsterdam, Amsterdam, the Netherlands.
Background: Predictive models in surgery promise to improve clinical care by anticipating complications, guiding decision-making, and supporting personalized treatment strategies. Although their potential to enhance outcomes and efficiency is substantial, their integration into clinical practice also raises profound ethical challenges.
Ethical Framework: These challenges span the entire lifecycle of predictive models from data collection and development to validation and clinical use.
Med Ref Serv Q
September 2025
Preston Medical Library, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA.
Costs for UpToDate, the library's primary point of care clinical tool, had increased to half of the acquisitions budget but without user affiliation data to facilitate cost sharing. A working group led by librarians was formed to review alternatives. Surveys indicated users preferred UpToDate and renewal was recommended by the working group, with costs being shared between the academic unit and the hospital.
View Article and Find Full Text PDFInt J Clin Pharm
September 2025
Porto Pharmacovigilance Centre, Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, 4200-319, Porto, Portugal.
Artificial intelligence (AI), particularly machine learning (ML), is increasingly influencing pharmacovigilance (PV) by improving case triage and signal detection. Several studies have reported encouraging performance, with high F1 scores and alignment with expert assessments, suggesting that AI tools can help prioritize reports and identify potential safety issues faster than manual review. However, integrating these tools into PV raises concerns.
View Article and Find Full Text PDFInt J Mol Sci
August 2025
Institute for Biomedical Research and Innovation (IRIB), National Research Council (CNR), 90146 Palermo, Italy.
VEXAS syndrome (Vacuoles, E1-enzyme, X-linked, Autoinflammation, and Somatic) is a recently identified late-onset autoinflammatory disorder characterized by a unique interplay between hematological and inflammatory manifestations. It results from somatic mutations in the gene, located on the short arm of the X chromosome. Initially, females were considered mere carriers, with the syndrome primarily affecting males over 50.
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