Evidence map›Paper›PMID 37168735›Full record

ReviewNature reviews bioengineering2023

Device integration of electrochemical biosensors.

Jie Wu, Hong Liu, Weiwei Chen, Biao Ma, Huangxian Ju

Abstract readReview
In one paragraph

Review in Nature reviews bioengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers.

0numbers the graph read from it
0cells of the map it votes in
196citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

196 citing papers in PubMed.

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  13. Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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136 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jie Wu *State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China.ORCID 0000-0003-1379-122X
Hong Liu *State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.ORCID 0000-0002-9841-1603
Weiwei ChenState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China.
Biao MaState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
Huangxian JuState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, China.ORCID 0000-0002-6741-5302

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical biosensors incorporate a recognition element and an electronic transducer for the highly sensitive detection of analytes in body fluids. Importantly, they can provide rapid readouts and they can be integrated into portable, wearable and implantable devices for point-of-care diagnostics; for example, the personal glucose meter enables at-home assessment of blood glucose levels, greatly improving the management of diabetes. In this Review, we discuss the principles of electrochemical biosensing and the design of electrochemical biosensor devices for health monitoring and disease diagnostics, with a particular focus on device integration into wearable, portable and implantable systems. Finally, we outline the key engineering challenges that need to be addressed to improve sensing accuracy, enable multiplexing and one-step processes, and integrate electrochemical biosensing devices in digital health-care pathways.

Indexed as

Diagnostic markersSensors

Identifiers

PMID37168735
PMCPMC9951169

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.