ReviewSensors (Basel, Switzerland)2022
Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning.
Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Is Breath Best? A Systematic Review on the Accuracy and Utility of Nanotechnology Based Breath Analysis of Ketones in Type 1 Diabetes.Biosensors · 2025Pooled it
- Trends and hotspots in the field of diabetic retinopathy imaging research from 2000-2023.Frontiers in medicine · 2024Pooled it
- A Novel Contactless Scanning Conductivity-Detection Approach for Moving Reaction Boundary Analysis in Electrophoresis Titration Sensors.Sensors (Basel, Switzerland) · 2026Article
- Advances in materials science for ocular diseases induced by cardiovascular risk factors.Frontiers in bioengineering and biotechnology · 2025Review
- Convolutional neural network-based sea lion optimization algorithm for the detection and classification of diabetic retinopathy.Acta diabetologica · 2023Article
- Rule extraction from biased random forest and fuzzy support vector machine for early diagnosis of diabetes.Scientific reports · 2022Article
- RNA-based diagnostic innovations: A new frontier in diabetes diagnosis and management.Diabetes & vascular disease researchReview
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this review, a selection of works on the sensing of biomarkers related to diabetes mellitus (DM) and diabetic retinopathy (DR) are presented, with the scope of helping and encouraging researchers to design sensor-array machine-learning (ML)-supported devices for robust, fast, and cost-effective early detection of these devastating diseases. First, we highlight the social relevance of developing systematic screening programs for such diseases and how sensor-arrays and ML approaches could ease their early diagnosis. Then, we present diverse works related to the colorimetric and electrochemical sensing of biomarkers related to DM and DR with non-invasive sampling (e.g., urine, saliva, breath, tears, and sweat samples), with a special mention to some already-existing sensor arrays and ML approaches. We finally highlight the great potential of the latter approaches for the fast and reliable early diagnosis of DM and DR.
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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.