Evidence map›Paper›PMID 41744722›Full record

ReviewBiosensors2026

Recent Advances in Microfluidic Chip Technology for Laboratory Medicine: Innovations and Artificial Intelligence Integration.

Hong Cai, Dongxia Wang, Yiqun Zhao, Chunhui Yang

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
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.

Hong CaiDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian 116023, China.ORCID 0009-0004-7696-2828
Dongxia WangDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian 116023, China.ORCID 0009-0006-6592-3959
Yiqun ZhaoDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian 116023, China.ORCID 0009-0004-4215-235X
Chunhui YangDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian 116023, China.ORCID 0009-0005-7721-0510

Funding

Dalian Life and Health Field Guidance Program Project 2024ZDJH01PT084Dalian Science and Technology Innovation Fund Program 2024JJ13PT070Liaoning Provincial Science and Technology Plan Joint Program Project 2025-MSLH-196United Foundation for Dalian Institute of Chemical Physics, Chinese Academy of Sciences and the Second Hospital of Dalian Medical University DMU-2&DICP UN202410
6 · The paper itself

Abstract

Microfluidic chip technologies, also known as lab-on-a-chip systems, have profoundly transformed laboratory medicine by enabling the miniaturization, automation, and rapid processing of complex diagnostic assays using minimal sample volumes. Recent advances in chip design, fabrication methods-including 3D printing, modular and flexible substrates-and biosensor integration have significantly enhanced the performance, sensitivity, and clinical applicability of these devices. Integration of advanced biosensors allows for real-time detection of circulating tumor cells, nucleic acids, and exosomes, supporting innovative applications in cancer diagnostics, infectious disease detection, point-of-care testing (POCT), personalized medicine, and therapeutic monitoring. Notably, the convergence of microfluidics with artificial intelligence (AI) and machine learning has amplified device automation, reliability, and analytical power, resulting in "smart" diagnostic platforms capable of self-optimization, automated analysis, and clinical decision support. Emerging applications in fields such as neuroscience diagnostics and microbiome profiling further highlight the broad potential of microfluidic technology. Here, we present findings from a comprehensive review of recent innovations in microfluidic chip design and fabrication, advances in biosensor and AI integration, and their clinical applications in laboratory medicine. We also discuss current challenges in manufacturing, clinical validation, and system integration, as well as future directions for translating next-generation microfluidic technologies into routine clinical and public health practice.

Indexed as

artificial intelligencelaboratory medicinemicrofluidic chip technologypoint-of-care testing

Identifiers

PMID41744722
PMCPMC12938137

What Socratic 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 Socratic graph.