Integrated Data analysis with smartphones, internet, and AI
Document Type
Article
Publication Date
1-1-2026
Abstract
Signal amplification and quantification are pivotal in enhancing the accuracy and sensitivity of lateral flow assays (LFAs). Smartphone-based LFAs are transforming biomedical diagnostics by enabling individuals to perform self-screening tests. This chapter explores the integration of data analysis with smartphones, the internet, and artificial intelligence (AI) in enhancing LFAs. LFAs are crucial for point-of-care diagnostics, but manual result interpretation can be error-prone. By utilizing smartphone cameras and processing power, results can be accurately captured and analyzed. Internet connectivity enables real-time data sharing and cloud-based analysis, while IoT devices facilitate continuous monitoring. AI algorithms improve diagnostic accuracy and predictive analytics for public health insights. Through case studies, we demonstrate the benefits of these technologies in various applications. The chapter also addresses challenges such as data privacy and technical limitations, highlighting the potential for improved diagnostic outcomes and disease management.
Publication Source (Journal or Book title)
Lateral Flow Assays for Rapid Point of Care Testing Recent Advances Emerging Trends and Future Direction
First Page
161
Last Page
172
Recommended Citation
Dey, M., Devireddy, R., & Gartia, M. (2026). Integrated Data analysis with smartphones, internet, and AI. Lateral Flow Assays for Rapid Point of Care Testing Recent Advances Emerging Trends and Future Direction, 161-172. https://doi.org/10.1016/B978-0-443-33156-5.00001-4