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Updated: Jul 9, 2026

Microfluidic Chip Fabrication and Method to Detect Influenza
Published on: March 26, 2013
Next-Generation Diagnostic Technologies for Dengue Virus Detection: Microfluidics, Biosensing, CRISPR, and AI
Salim El Kabbani1, Gameel Saleh1
1Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Dengue diagnosis needs improvement. This review covers current and emerging technologies, like biosensors and AI, to enable faster, more accessible dengue fever detection and reduce global disease impact.
Area of Science:
- Medical Entomology
- Infectious Diseases
- Biotechnology
Background:
- Dengue fever affects over 400 million people globally each year.
- High transmission rates in tropical/subtropical regions necessitate early diagnosis for control.
- Conventional diagnostic methods face limitations including cost, time, and accessibility.
Purpose of the Study:
- To review current dengue diagnostic technologies and their limitations.
- To explore recent advances in biosensing and AI for dengue diagnostics.
- To highlight the need for improved, field-deployable diagnostic solutions.
Main Methods:
- Review of existing literature on dengue diagnostic techniques.
- Analysis of target analytes (viral RNA, NS1, antibodies) and biofluids (blood, serum, plasma, urine).
- Examination of emerging biosensing platforms (optical, electrochemical, microfluidic, CRISPR-based) and AI integration.
Main Results:
- Conventional methods (RT-PCR, ELISA) are accurate but costly and slow.
- New biosensing technologies offer potential for rapid, sensitive, and field-deployable diagnostics.
- AI integration can enhance data analysis and diagnostic accuracy.
Conclusions:
- There is a critical need for accurate, scalable, and field-deployable dengue diagnostic tools.
- Advancements in biosensing and AI are promising for early dengue detection.
- Improved diagnostics are essential to reduce the global burden of dengue fever.
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