Advancing Colorimetric Analysis in Enzyme-Linked Immunosorbent Assays: Harnessing Nonlinear Regression for Improved Accuracy and Predictive Performance
range: 0.923-0.996). Root mean square error was reduced by over 98%, and Spearman and Pearson correlation coefficients approached unity, demonstrating excellent trend fidelity and linear alignment with FDA-certified ELISA readers (Epoch and Tecan). The model's robustness was further confirmed through k-fold cross-validation and rigorous statistical analysis. This advancement positions our platform as a powerful candidate for decentralized diagnostics and high-throughput screening, capable of operating reliably across different smartphones and lighting conditions.
Authors
- Akram Mirzaei (ORCID: https://orcid.org/0000-0003-2219-999X)
- Aryanaz Faghih Nasiri (ORCID: https://orcid.org/0000-0002-9302-2836)
- Fatemeh Khatami (ORCID: https://orcid.org/0000-0002-6311-1336)
- Mohammadreza Kolahdouz (ORCID: https://orcid.org/0000-0001-6992-6950)
- Seyed Mohammad Kazem Aghamir (ORCID: https://orcid.org/0000-0003-1611-0362)
- Shaghayegh Mirhosseini (ORCID: https://orcid.org/0000-0002-7385-8142)
- Nathan S. Swami (ORCID: https://orcid.org/0000-0002-0492-1160)
Institutions
- University of Tehran (IR)
- University of Virginia (US)
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- ACS Omega
- Published
- 2026-04-22
- DOI
- https://doi.org/10.1021/acsomega.5c10509
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health