Machine Learning-Based Protein Microarray Digital Assay Analysis

Yujing Song, Jingyang Zhao, Tao Cai, Shiuan-Haur Su, Erin Sandford, Christopher Flora, Benjamin H. Singer, Monalisa Ghosh, Sung Won Choi, Muneesh Tewari, Katsuo Kurabayashi
2020 · doi:10.1101/2020.08.04.236448
preprint OA: closed
📄 Open PDF View at publisher

Abstract

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, we developed a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay achieved 14-plexed biomarker detection at concentrations < 10pg/mL with a sample volume < 10 μL, including all processes from sampling to analyzed data delivery within 30 min, while only requiring a 5-min assay incubation. The assay procedure applied both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduced errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 14 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy manifested the powerful biomarker profiling capability and great potential of the assay for its translation to near-real-time bedside immune status monitoring.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

References (33)

Source provenance

crossref
last seen: 2026-05-24T01:00:08.302826+00:00
europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-07-26T06:48:27.953686+00:00