Evidence map›Paper›PMID 40310427›Full record

ReviewDiagnostics (Basel, Switzerland)2025

Biosensors, Artificial Intelligence Biosensors, False Results and Novel Future Perspectives.

Georgios Goumas, Efthymia N Vlachothanasi, Evangelos C Fradelos, Dimitra S Mouliou

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  4. AI-nanotech synergies: recent advances in sustainable bio-manufacturing.World journal of microbiology & biotechnology · 2026
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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

4 authors.

Georgios GoumasSchool of Public Health, University of West Attica, 12243 Athens, Greece.ORCID 0009-0008-5940-2043
Efthymia N VlachothanasiLaboratory of Clinical Nursing, Department of Nursing, University of Thessaly Larissa, 41334 Larissa, Greece.
Evangelos C FradelosLaboratory of Clinical Nursing, Department of Nursing, University of Thessaly Larissa, 41334 Larissa, Greece.ORCID 0000-0003-0244-9760
Dimitra S MouliouIndependent Researcher, 38500 Volos, Greece.ORCID 0000-0003-3179-4010

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical biosensors have set the basis of medical diagnostics, and Artificial Intelligence (AI) has boosted diagnostics to a great extent. However, false results are evident in every method, so it is crucial to identify the reasons behind a possible false result in order to control its occurrence. This is the first critical state-of-the-art review article to discuss all the commonly used biosensor types and the reasons that can give rise to potential false results. Furthermore, AI is discussed in parallel with biosensors and their misdiagnoses, and again some reasons for possible false results are discussed. Finally, an expert opinion with further future perspectives is presented based on general expert insights, in order for some false diagnostic results of biosensors and AI biosensors to be surpassed.

Indexed as

AIAI biosensorsArtificial IntelligenceArtificial Intelligence biosensorsbiosensorsfalse negativefalse positivefalse resultsfalse test resultsnovel biosensor

Identifiers

PMID40310427
PMCPMC12025796

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.