Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning.
diabetes mellitus
diabetic retinopathy
early detection and diagnosis
glucose sensing
machine learning
point-of-care
screening
sensor arrays
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
18 Jan 2022
18 Jan 2022
Historique:
received:
31
10
2021
revised:
20
12
2021
accepted:
26
12
2021
entrez:
15
2
2022
pubmed:
16
2
2022
medline:
17
2
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 35161465
pii: s22030718
doi: 10.3390/s22030718
pmc: PMC8839630
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
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