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Smartphone-integrated portable microfluidic platform for liver biomarker quantification using deep learning.

Neha Ingole1, Sangeeta Palekar2, Madhusudan B Kulkarni3

  • 1Department of Electronics Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, 440013, Maharashtra, India.

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|November 22, 2025
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Summary

A new smartphone platform uses 3D-printed microfluidics and AI to accurately measure liver biomarkers like bilirubin and ALT/AST. This portable device enables decentralized liver function testing, crucial for remote healthcare settings.

Keywords:
Deep learningLiver biomarkersMicrofluidicsPoint of care testingSmartphone-based sensing

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Area of Science:

  • Biomedical Engineering
  • Medical Diagnostics
  • Mobile Health Technology

Background:

  • Accurate liver biomarker testing is vital for diagnosing and monitoring hepatic dysfunction, especially in underserved regions.
  • Current methods often require centralized labs, limiting accessibility in resource-constrained settings.

Purpose of the Study:

  • To develop a novel, smartphone-integrated colorimetric sensing platform for quantitative liver biomarker analysis.
  • To enable decentralized and cost-effective liver function assessment using microfluidics, deep learning, and mobile health.

Main Methods:

  • A stereolithography (SLA) 3D-printed microfluidic flow cell was designed for low reagent consumption and optical clarity.
  • Chromogenic reactions for biomarkers were imaged using various smartphones within a controlled lighting enclosure.
  • A convolutional neural network (CNN) analyzed the images for quantitative biomarker estimation, with a smartphone adaptability framework for cross-device consistency.

Main Results:

  • The platform achieved clinically relevant detection ranges for direct/total bilirubin (0.1-20 mg/dL) and ALT/AST (10-300 U/L).
  • Limits of detection were as low as 0.1 mg/dL for bilirubin and 2.5 U/L for AST.
  • High accuracy was demonstrated with an average R² of 0.997 and repeatability with coefficients of variation under 3%.

Conclusions:

  • This innovative, cost-effective, and portable system provides precise liver function assessment.
  • The smartphone-integrated platform is ideal for rural healthcare and mobile diagnostics, enhancing early disease detection and monitoring.