AIMC Topic: Lab-On-A-Chip Devices

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Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing.

Scientific reports
Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism's development. Although current testing primarily relies on large mammalian models, the emergence of new approach methodologies (NAMs) is encourag...

An integrated microflow cytometry platform with artificial intelligence capabilities for point-of-care cellular phenotype analysis.

Biosensors & bioelectronics
The EZ DEVICE is an integrated fluorescence microflow cytometer designed for automated cell phenotyping and enumeration using artificial intelligence (AI). The platform consists of a laser diode, optical filter, objective lens, CMOS image sensor, and...

Transformative laboratory medicine enabled by microfluidic automation and artificial intelligence.

Biosensors & bioelectronics
Laboratory medicine provides pivotal medical information through analyses of body fluids and tissues, and thus, it is essential for diagnosis of diseases as well as monitoring of disease progression. Despite its universal importance, the field is cur...

Convolutional neural network for colorimetric glucose detection using a smartphone and novel multilayer polyvinyl film microfluidic device.

Scientific reports
Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overall health. In this endeavor, we have designed a novel, affordable point-of-care diagnostic device uti...

Combining array-assisted SERS microfluidic chips and machine learning algorithms for clinical leukemia phenotyping.

Talanta
The disease progression and treatment options of leukemia between different subtypes vary considerably, emphasizing the importance of phenotyping. However, early typing of leukemia remains challenging due to the lack of highly sensitive and specific ...

In-vitro blood purification using tiny pinch holographic optical tweezers based on deep learning.

Biosensors & bioelectronics
In-vitro blood purification is essential to a wide range of medical treatments, requiring fine-grained analysis and precise separation of blood components. Despite existing methods that can extract specific components from blood by size or by magneti...

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

International journal of biological macromolecules
User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited environments. Nevertheless, existing sensing strategies require professional technicians and expensi...

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

ACS nano
CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput,...

Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions.

ACS sensors
Point-of-Care-Testing (PoCT) has emerged as an essential component of modern healthcare, providing rapid, low-cost, and simple diagnostic options. The integration of Machine Learning (ML) into biosensors has ushered in a new era of innovation in the ...

Integrating machine learning and biosensors in microfluidic devices: A review.

Biosensors & bioelectronics
Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research to Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvir...