Literature Collection

Objective: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors. This systematic review examines the application of artificial intelligence (AI) in diagnosing ASD, focusing on pediatric populations aged 0-18 years. Materials and methods: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Inclusion criteria encompassed studies applying AI techniques for ASD diagnosis, primarily evaluated using metriclike accuracy. Non-English articles and studies not focusing on diagnostic applications were excluded. The literature search covered PubMed, ScienceDirect, CENTRAL, ProQuest, Web of Science, and Google Scholar up to November 9, 2024. Bias assessment was performed using the Joanna Briggs Institute checklist for critical appraisal. Results: The review included 25 studies. These studies explored AI-driven approaches that demonstrated high accuracy in classifying ASD using various data modalities, including visual (facial, home videos, eye-tracking), motor function, behavioral, microbiome, genetic, and neuroimaging data. Key findings highlight the efficacy of AI in analyzing complex datasets, identifying subtle ASD markers, and potentially enabling earlier intervention. The studies showed improved diagnostic accuracy, reduced assessment time, and enhanced predictive capabilities. Conclusion: The integration of AI technologies in ASD diagnosis presents a promising frontier for enhancing diagnostic accuracy, efficiency, and early detection. While these tools can increase accessibility to ASD screening in underserved areas, challenges related to data quality, privacy, ethics, and clinical integration remain. Future research should focus on applying diverse AI techniques to large populations for comparative analysis to develop more robust diagnostic models.

BACKGROUND: Approximately 50 million individuals across the globe are impacted by epilepsy, leading to fear, discrimination, psychiatric issues, high costs, and social stigma. Proper diagnosis and treatment could allow up to 70% of those affected to live seizure-free. Community pharmacists have significant potential to actively participate in epilepsy patient care, beyond merely dispensing medications. The objective of this study was to systematically review and assess the roles of pharmacists in epilepsy care, focusing on pharmacist-led interventions and services for patients with epilepsy. METHODS: Following PRISMA 2020 guidelines, the review included cross-sectional, retrospective cohort, and qualitative/quantitative studies on pharmacist-led epilepsy interventions in community and outpatient settings. Searches were conducted in Scopus, PubMed Central, and Science Direct for studies published through the end of 2023. Two evaluators independently reviewed and chose studies, and the data was analysed using Microsoft Excel®. Quality assessment was performed using the MMAT tool. RESULTS: Five eligible studies were included, covering 457 participants. Studies originated from the USA (n = 3), Netherlands (n = 1), and Palestine (n = 1). They evaluated pharmacist-led interventions in epilepsy, including medication adherence, quality of life, and pharmacist's integration in epilepsy care. CONCLUSION: This review underscores the possible contributions of pharmacists in epilepsy care, stressing the importance of pharmacist-led interventions to enhance medication adherence and the quality of life for individuals with epilepsy. Future research should evaluate the effectiveness and cost-effectiveness of these services, including disease management and patient education. Increasing awareness among pharmacists and patients about pharmacists' contributions is crucial for improving epilepsy care.