Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date: Jun 17, 2024

Abstract

Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection is a public health priority but challenging. In this study, an adhesive, soft on-skin sensor with low electrode-skin contact impedance for early-stage NAFLD detection is fabricated. A method is developed to synthesize platinum nanoparticles and reduced graphene quantum dots onto the on-skin sensor to reduce electrode-skin contact impedance by increasing double-layer capacitance, thereby enhancing detection accuracy. Furthermore, an attention-based deep learning algorithm is introduced to differentiate impedance signals associated with early-stage NAFLD in high-fat-diet-fed low-density lipoprotein receptor knockout (Ldlr) mice compared to healthy controls. The integration of an adhesive, soft on-skin sensor with low electrode-skin contact impedance and the attention-based deep learning algorithm significantly enhances the detection accuracy for early-stage NAFLD, achieving a rate above 97.5% with an area under the receiver operating characteristic curve (AUC) of 1.0. The findings present a non-invasive approach for early-stage NAFLD detection and display a strategy for improved early detection through on-skin electronics and deep learning.

Authors

  • Kaidong Wang
    Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Samuel Margolis
    Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Jae Min Cho
    Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Shaolei Wang
    Department of Orthopaedic Surgery, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, China.
  • Brian Arianpour
    Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Alejandro Jabalera
    Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Junyi Yin
    Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Wen Hong
    Department of Materials Science and Engineering, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Yaran Zhang
    Department of Neurosurgery, Amsterdam University Medical Centers, Cancer Center Amsterdam, Brain Tumor Center Amsterdam, Amsterdam, The Netherlands.
  • Peng Zhao
    Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
  • Enbo Zhu
    Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Srinivasa Reddy
    Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • Tzung K Hsiai
    School of Medicine, University of California Los Angeles, Los Angeles, CA 90073, USA. THsiai@mednet.ucla.edu.

Keywords

External Resources

Popular Topics
Recent Journals