پوشیدنی‌های مبتنی بر هوش مصنوعی: انقلابی در تلاش‌های جهانی برای پیشگیری از شیوع لیشمانیازیس
کد: G-1395
نویسندگان: امیرمحمد فلاحی لیما *, Kimia Asadollahi Razi ℗, امیررضا شاکری
زمان بندی: زمان بندی نشده!
برچسب: دستگاه های پوشیدنی و کاشتنی
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Introduction: Leishmaniasis, a vector-borne disease caused by Leishmania parasites, considers a significant global health challenge, particularly in endemic regions. Current preventive measures, such as insecticides, have limitations in efficacy and scalability. The integration of artificial intelligence (AI) with wearable technology offers a novel approach to combating leishmaniasis by enabling real-time monitoring, early detection, and insect-repelling capabilities. This review explores the potential of AI-driven wearables in reducing leishmaniasis outbreaks through innovative applications such as smart repellents, predictive analytics, and personalized protection. Materials and Methods: A systematic review of existing literature was conducted, focusing on AI applications in wearable technology for health monitoring and vector control. Sources included peer-reviewed journals, conference proceedings, and case studies published between 2018 and 2024. Studies on AI-driven diagnostic tools for leishmaniasis, wearable repellent technologies, and spatial repellents were analyzed. Key metrics such as device efficacy, AI algorithm performance (e.g., sensitivity, specificity), and user adoption rates were evaluated. Additionally, mathematical modeling studies assessing the epidemiological impact of repellents and wearables were reviewed to gauge their potential in outbreak prevention. Results: AI-powered wearables demonstrated significant advancements in vector control and disease prevention. For example, spatial repellents integrated into wearable devices achieved very good protection against sandflies. AI algorithms used in diagnostic tools for cutaneous leishmaniasis achieved high accuracy rates. Predictive analytics enabled by wearables provided actionable insights for targeted interventions in high-risk populations. Furthermore, mathematical models indicated that widespread adoption of repellent wearables could avert up infections during outbreaks with moderate transmission rates. Conclusion: AI-driven wearable devices hold immense potential to revolutionize leishmaniasis prevention with effective vector control strategies. These technologies offer scalable solutions for endemic regions by reducing reliance on traditional methods like insecticides . However, challenges such as affordability, and infrastructure limitations must be addressed to ensure widespread adoption. Future research should focus on optimizing AI algorithms for resource-limited settings, enhancing device durability, and conducting large-scale field trials to validate their epidemiological impact. By using AI-powered wearables, global efforts to combat leishmaniasis can achieve greater precision and sustainability.
کلمات کلیدی
Leishmaniasis, Vector Control, AI-driven Wearables, Parasites
