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A Microfluidic-based Electrochemical Biochip for Label-free DNA Hybridization Analysis
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Emerging Trends in Artificial Intelligence-Integrated Biochip Technologies for Biomedical Applications.

Muniyandi Maruthupandi1, Nae Yoon Lee2

  • 1Department of BioNano Convergence, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Gyeonggi-do, Republic of Korea.

Micromachines
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) integrated with biochip technology enhances disease diagnostics. This approach improves accuracy and speed for detecting neurological disorders, diabetes, and cancer, especially in underserved regions.

Keywords:
artificial intelligencebacteriabiochipdeep learningdiabetesdiagnosticsdrug deliverymachine learningneurological disordersvirus

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Area of Science:

  • Biomedical Diagnostics
  • Biochip Technology
  • Artificial Intelligence

Background:

  • Major global health concerns include neurological disorders, diabetes, cancer, and infectious diseases, particularly in low- and middle-income countries.
  • Conventional biochip platforms face limitations in complex instrumentation and large dataset handling for diagnostics.

Purpose of the Study:

  • To evaluate the integration of artificial intelligence (AI) with biochip technology for improved biomedical diagnostics.
  • To address limitations of conventional biochip sensing platforms in handling complex data and instrumentation.

Main Methods:

  • Systematic analysis of recent advances in AI-integrated biochips (spectroscopic, paper-based, lab-on-chip, microfluidic).
  • Integration of machine learning, deep learning, and reinforcement learning models with biosensor outputs (electrochemical, fluorescence, colorimetric).

Main Results:

  • AI models simplify pattern recognition, feature extraction, and automated data processing from biosensor signals.
  • Studies show improved real-time diagnostic sensitivity and accuracy in various biomedical applications.

Conclusions:

  • AI-integrated biochips offer enhanced disease detection and clinical decision-making capabilities.
  • Future perspectives include developing explainable, robust, and smartphone-assisted AI-biochips for rapid diagnostics.