ReviewBiosensors2024
Machine Learning-Driven Innovations in Microfluidics.
Review in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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.
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.
Who cites it
18 citing papers in PubMed.
- Integrated microfluidic biosensors: shaping the future of quantitative life sciences and on-chip molecular diagnostics.Lab on a chip · 2026Review
- Developing Micro/Nanostructured Fluidic Mixing Technology for Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Smart label-free SPR biosensing platform for hemoglobin and urine glucose detection via machine learning.Scientific reports · 2026Article
- Lab-on-a-Chip and Microfluidics Technologies for Nano Drug Delivery.Bioengineering (Basel, Switzerland) · 2026Review
- Recent Advances in MEMS Actuators for Microfluidic Applications: Emerging Designs, Multiphysics Modeling, and Performance Optimization.Micromachines · 2026Review
- Recent Advances in Microfluidic Chip Technology for Laboratory Medicine: Innovations and Artificial Intelligence Integration.Biosensors · 2026Review
- Tailoring human joint-on-a-chip: from biological principles, materials, to disease modeling.Materials today. Bio · 2026Review
- Mechanistic insights of smart biofilms in environmental bio-monitoring: from growth to detection.Microbial cell factories · 2026Review
- Artificial Intelligence-Aided Microfluidic Cell Culture Systems.Biosensors · 2025Review
- Enhancing Microparticle Separation Efficiency in Acoustofluidic Chips via Machine Learning and Numerical Modeling.Sensors (Basel, Switzerland) · 2025Article
- AI-Enabled Microfluidics for Respiratory Pathogen Detection.Sensors (Basel, Switzerland) · 2025Review
- Integrated Photonic Biosensors: Enabling Next-Generation Lab-on-a-Chip Platforms.Nanomaterials (Basel, Switzerland) · 2025Review
- Preliminary Study on Sensor-Based Detection of an Adherent Cell's Pre-Detachment Moment in a MPWM Microfluidic Extraction System.Sensors (Basel, Switzerland) · 2025Article
- Recent Advances in Pretreatment Methods and Detection Techniques for Veterinary Drug Residues in Animal-Derived Foods.Metabolites · 2025Review
- Biosensor Technologies for Water Quality: Detection of Emerging Contaminants and Pathogens.Biosensors · 2025Review
- Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design.Biosensors · 2025Article
- Multianalyte nano-biosensor diagnostics: advances through microfluidic and AI integration.Frontiers in bioengineering and biotechnology · 2025Review
- Microfluidics and molecular diagnostics in renal cell carcinoma: advances, challenges, and future directions.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Microfluidic devices have revolutionized biosensing by enabling precise manipulation of minute fluid volumes across diverse applications. This review investigates the incorporation of machine learning (ML) into the design, fabrication, and application of microfluidic biosensors, emphasizing how ML algorithms enhance performance by improving design accuracy, operational efficiency, and the management of complex diagnostic datasets. Integrating microfluidics with ML has fostered intelligent systems capable of automating experimental workflows, enabling real-time data analysis, and supporting informed decision-making. Recent advances in health diagnostics, environmental monitoring, and synthetic biology driven by ML are critically examined. This review highlights the transformative potential of ML-enhanced microfluidic systems, offering insights into the future trajectory of this rapidly evolving field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.