ReviewMikrochimica acta2023
A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification.
Review in Mikrochimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Species-specific discrimination of bacterial biofilms using a ratiometric fluorescence sensor array and machine learning.Sensors & diagnostics · 2026Article
- Integration of Artificial Intelligence in Biosensors for Enhanced Detection of Foodborne Pathogens.Biosensors · 2025Review
- A novel MOF combined with dummy molecularly imprinted polymer paper-based colorimetric sensor equipped with a smartphone detector for sensitive, portable, and on-site detection of organophosphorus pesticides.Mikrochimica acta · 2025Article
- Sensor Arrays: A Comprehensive Systematic Review.Sensors (Basel, Switzerland) · 2025Review
- Design Principles of Nanosensors for Multiplex Detection of Contaminants in Food.Small (Weinheim an der Bergstrasse, Germany) · 2025Review
- Tuning multispectral fluorescence quantum dot-based identification of short-length amyloid β peptides by applying Cu(II) ions.Mikrochimica acta · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.
Indexed as
Identifiers
37880465What 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.