ReviewAnnals of biomedical engineering2020
Scalable Signature-Based Molecular Diagnostics Through On-chip Biomarker Profiling Coupled with Machine Learning.
Review in Annals of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Microfluidics as a promising technology for personalized medicine.BioImpacts : BI · 2025Review
- AlphaFold2 in biomedical research: facilitating the development of diagnostic strategies for disease.Frontiers in molecular biosciences · 2024Review
- Biomimetic Microfluidic Platforms for the Assessment of Breast Cancer Metastasis.Frontiers in bioengineering and biotechnology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Molecular diagnostics have traditionally relied on discrete biological substances as diagnostic markers. In recent years however, advances in on-chip biomarker screening technologies and data analytics have enabled signature-based diagnostics. Such diagnostics aim to utilize unique combinations of multiple biomarkers or diagnostic 'fingerprints' rather than discrete analyte measurements. This approach has shown to improve both diagnostic accuracy and diagnostic specificity. In this review, signature-based diagnostics enabled by microfluidic and micro-/nano- technologies will be reviewed with a focus on device design and data analysis pipelines and methodologies. With increasing amounts of data available from microfluidic biomarker screening, isolation, and detection platforms, advanced data handling and analytics approaches can be employed. Thus, current data analysis approaches including machine learning and recent advances with image processing, along with potential future directions will be explored. Lastly, the needs and gaps in current literature will be elucidated to inform future efforts towards development of molecular diagnostics and biomarker screening technologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.