Evidence map›Paper›PMID 40522091›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2025

The Role of Artificial Intelligence in Advancing Biosensor Technology: Past, Present, and Future Perspectives.

Tuğba Akkaş, Mahshid Reshadsedghi, Mustafa Şen, Volkan Kılıç, Nesrin Horzum

Abstract readReview
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
–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

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Electrochemical in-biosensing computing.National science review · 2026
    Article
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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

5 authors.

Tuğba AkkaşDepartment of Biomedical Engineering Graduate Program, Izmir Katip Celebi University, Izmir, 35620, Turkey.
Mahshid ReshadsedghiDepartment of Electrical and Electronics Engineering Graduate Program, Izmir Katip Celebi University, Izmir, 35620, Turkey.ORCID https://orcid.org/0009-0001-1559-5313
Mustafa ŞenDepartment of Biomedical Engineering Graduate Program, Izmir Katip Celebi University, Izmir, 35620, Turkey.
Volkan KılıçDepartment of Electrical and Electronics Engineering Graduate Program, Izmir Katip Celebi University, Izmir, 35620, Turkey.ORCID https://orcid.org/0000-0002-3164-1981
Nesrin HorzumDepartment of Engineering Science, Izmir Katip Celebi University, Izmir, 35620, Turkey.ORCID https://orcid.org/0000-0002-2782-0581

Funding

The Scientific and Technological Research Council of Turkey (TÜBİTAK) 123M411
6 · The paper itself

Abstract

Integrating artificial intelligence (AI) into biosensor technology enables data processing, quantitative analysis, real-time decision-making, and adaptive sensing capabilities through advanced pattern recognition and predictive modeling. In addition, AI has the potential to drive innovation in the design of advanced materials for biosensing applications by reducing the reliance on trial-and-error methods. This review explores the transformative impact of AI on biosensor technology in the context of historical development, current status, and future prospects. It begins with an overview of the evolution of AI, biosensor technology, and their integration. Comparative analysis of AI-driven innovations in optical, fluorometric, and electrochemical biosensors is presented, highlighting how AI can improve sensor performance. The role of advanced materials on the development of AI-assisted biosensors is also discussed as the choice of material has a profound effect on biosensor capabilities. Applications of AI-assisted biosensors are comprehensively explored across healthcare, environmental monitoring, food safety, and agriculture. This study concludes by addressing challenges, opportunities, ethical concerns, and future research directions, providing a comprehensive and up-to-date resource for researchers.

Indexed as

Artificial IntelligenceBiosensing TechniquesHumansartificial intelligencebiosensorsInternet of Things (IoT)wearable devices

Identifiers

PMID40522091
PMCPMC12392873

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.