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Purpose <p>This work aimed to create a medical device for quantifying total bilirubin in human samples, using artificial intelligence as a diagnostic tool.</p> Methods <p>The device uses the principle of chromatography for sample flow, enabling the assessment of bilirubin concentration in human serum samples from both adults and neonates. With the integration of artificial intelligence, the device reading and result characterization were achieved through a dedicated reading instrument. The device’s performance was evaluated using the CLSI EP15-A3 as a testing metric to assess the results’ accuracy. Controls and samples were used to enable the clinical tests and the development of AI standardization.</p> Results <p>Following performance studies, the device demonstrated linearity from 0.7 to 20&#xa0;mg/dL of total bilirubin. Precision studies indicated an intra-run variation of 7.6% and an intra-laboratory variation of 6.9%. Clinical performance data established a Pearson correlation (r) of 0.996 and a <i>t</i>-test of 0.8 (significant value, <i>p</i> &gt; 0.05). Stability studies concluded that the product is valid for 12&#xa0;months post-manufacture, achieving the established performance with rapid and accurate results in under 10&#xa0;min.</p> Conclusion <p>The development of this point-of-care device for bilirubin detection brings a practical and innovative solution. With reliable performance comparable to the biochemical reference method, the device integrates advanced technologies while requiring fewer resources and less training. This approach expands healthcare access, especially in remote areas, promoting efficient and accessible diagnostics through portable technology.</p>

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AI-based point-of-care device for total bilirubin quantification

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • Rafael Benedetti,
  • Ava Gevaerd,
  • Henrique Cunha Carvalho,
  • Marcus Vinicius Mazega Figueredo,
  • Frieda Saicla Barros

摘要

Purpose

This work aimed to create a medical device for quantifying total bilirubin in human samples, using artificial intelligence as a diagnostic tool.

Methods

The device uses the principle of chromatography for sample flow, enabling the assessment of bilirubin concentration in human serum samples from both adults and neonates. With the integration of artificial intelligence, the device reading and result characterization were achieved through a dedicated reading instrument. The device’s performance was evaluated using the CLSI EP15-A3 as a testing metric to assess the results’ accuracy. Controls and samples were used to enable the clinical tests and the development of AI standardization.

Results

Following performance studies, the device demonstrated linearity from 0.7 to 20 mg/dL of total bilirubin. Precision studies indicated an intra-run variation of 7.6% and an intra-laboratory variation of 6.9%. Clinical performance data established a Pearson correlation (r) of 0.996 and a t-test of 0.8 (significant value, p > 0.05). Stability studies concluded that the product is valid for 12 months post-manufacture, achieving the established performance with rapid and accurate results in under 10 min.

Conclusion

The development of this point-of-care device for bilirubin detection brings a practical and innovative solution. With reliable performance comparable to the biochemical reference method, the device integrates advanced technologies while requiring fewer resources and less training. This approach expands healthcare access, especially in remote areas, promoting efficient and accessible diagnostics through portable technology.