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http://dx.doi.org/10.1111/liv.70320 | DOI Listing |
Front Psychiatry
August 2025
TransLab Research Group, Department of Medical Sciences, University of Girona, Girona, Spain.
Introduction: Clinical practice guidelines (CPGs) have several limitations, namely: obsolescence, lack of personalization, and insufficient patient participation. These factors may contribute to suboptimal treatment recommendation compliance and poorer clinical outcomes. APPRAISE-RS is an adaptation of the GRADE heuristic designed to generate CPG-like treatment recommendations that are automated, updated, personalized, participatory, and explanatory using a symbolic AI approach.
View Article and Find Full Text PDFLiver Int
October 2025
Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu, China.
Brain Sci
July 2025
Department of Economic, Psychological, Communication, Education and Motor Sciences, Università Degli Studi Niccolò Cusano, 00166 Rome, Italy.
: While artificial intelligence (AI) is rapidly transforming education, its specific effectiveness for students with learning disabilities (LD) requires rigorous evaluation. This systematic review aims to assess the efficacy of AI-based educational interventions for students with LD, with a specific focus on the methodological quality and risk of bias of the available evidence. : A systematic search was conducted across seven major databases (Google Scholar, ScienceDirect, APA PsycInfo, ERIC, Scopus, PubMed) for experimental studies published between 2022 and 2025.
View Article and Find Full Text PDFInt Angiol
June 2025
Faculty of Medicine, University of Porto, Porto, Portugal.
Introduction: The purpose of this review was to critically evaluate the current literature on AI applicability to developing prediction models for cerebrovascular events in patients with carotid artery stenosis using standardized tools.
Evidence Acquisition: A systematic review was performed in accordance with the Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. Critical appraisal was conducted using PROBAST risk-of-bias and the TRIPOD-AI reporting adherence tools.
Pain Manag Nurs
August 2025
Nursing Department, Dalian University Affiliated Xinhua Hospital, Dalian, China. Electronic address:
Objectives: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizing the unique contributions of specialized nurses.
Design: A systematic review was conducted to examine the integration of AI in the management of KOA, with a specific focus on implications for nursing practice.
Methods: This review followed established systematic review protocols.