AI-Enabled Microfluidics Respiratory Pathogen Detection is a M.Tech project topic for Biotechnology & Biomedical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
AI-Enabled Microfluidics Respiratory Pathogen Detection Project Details
| Abstract |
This study focuses on combining artificial intelligence (AI) systems with microfluidics technology to identify respiratory pathogens. The rapid detection of diagnostic technologies for respiratory infectious diseases (COVID-19, influenza, and tuberculosis) is a significant global health concern and is needed for pathogen detection and diagnosis. Microfluidics technology enables point-of-care testing with its sample-in answer-out capabilities. However, microfluidics technology does not address clinical challenges because of sample complexities, low target abundance, and required multiplexing. Because of these challenges, combining AI with microfluidics is transformative. AI can design, automate sample pre-processing, enhance diagnostic signal interpretation, and offer real-time feedback within microfluidic devices. The investigation focuses on AI-enhanced techniques to address unique challenges within
specific functional layers of respiratory pathogen diagnostics, including microchip design, fluidic control, signal analysis, predictive analytics, and smart device-connected decision support systems. AI integration into diagnostic tools is intended to illustrate clinical insight, improved adaptability, and data efficiencies diagnostic value. Future advancements may involve integrated sensing chips, privacy-preserving machine learning, and multi-modal data fusion (to ensure sustained clinical reliability).
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| Reference Paper |
AI-Enabled Microfluidics for Respiratory Pathogen Detection |
| Domain |
Biotechnology & Biomedical Engineering |
| Sub-Domain |
Bioprocess Engineering / Downstream Processing / Bioseparation |
| PDF Download |
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