AIMC Topic: Lab-On-A-Chip Devices
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Advanced droplet microfluidic platform for high-throughput screening of industrial fungi.
Biosensors & bioelectronics
May 16, 2025
Industrial fungi are pivotal candidates for the production of a diverse array of bioproducts. To enhance their productivity, these strains are frequently subjected to genetic modifications. Following transformation, the selection of optimal productio...
Deep learning-assisted 10-μL single droplet-based viscometry for human aqueous humor.
Biosensors & bioelectronics
May 2, 2025
Probing the viscosity of human aqueous humor is crucial for optimizing micro-tube shunts in glaucoma treatment. However, conventional viscometers are not suitable for aqueous humor due to the limited sample volume-only tens of microliters-that can be...
Optimizing microfluidic chip for rapid SARS-CoV-2 detection using Taguchi method and artificial neural network PSO.
Scientific reports
Apr 23, 2025
Microfluidic biosensors offer a promising solution for real-time analysis of coronaviruses with minimal sample volumes. This study optimizes a biochip for the rapid detection of SARS-CoV-2 using the Taguchi orthogonal table L(3), which comprises nine...
Artificial intelligence in preclinical research: enhancing digital twins and organ-on-chip to reduce animal testing.
Drug discovery today
Apr 17, 2025
Artificial intelligence (AI) is reshaping preclinical drug research offering innovative alternatives to traditional animal testing. Advanced techniques, including machine learning (ML), deep learning (DL), AI-powered digital twins (DTs), and AI-enhan...
Deep-Learning-Assisted Microfluidic Immunoassay via Smartphone-Based Imaging Transcoding System for On-Site and Multiplexed Biosensing.
Nano letters
Apr 9, 2025
Point-of-care testing (POCT) with multiplexed capability, ultrahigh sensitivity, affordable smart devices, and user-friendly operation is critically needed for clinical diagnostics and food safety. This study presents a deep-learning-assisted microfl...
Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes.
ACS sensors
Apr 1, 2025
Lung cancer exhibits strong heterogeneity, and its early diagnosis and precise subtyping are of great importance, as they can increase the ability to deliver personalized medicines by tailoring therapy regimens. Tissue biopsy, albeit the gold standar...
Advancements in Circulating Tumor Cell Detection for Early Cancer Diagnosis: An Integration of Machine Learning Algorithms with Microfluidic Technologies.
Biosensors
Mar 29, 2025
Circulating tumor cells (CTCs) are vital indicators of metastasis and provide a non-invasive method for early cancer diagnosis, prognosis, and therapeutic monitoring. However, their low prevalence and heterogeneity in the bloodstream pose significant...
Transformative biomedical devices to overcome biomatrix effects.
Biosensors & bioelectronics
Mar 12, 2025
The emergence of high-performance biomedical devices and sensing technologies highlights the technological advancements in the field. Recently during COVID-19 pandemic, biosensors played an important role in medical diagnostics and disease monitoring...
Sensing the Future of Thrombosis Management: Integrating Vessel-on-a-Chip Models, Advanced Biosensors, and AI-Driven Digital Twins.
ACS sensors
Mar 11, 2025
Thrombotic events, such as strokes and deep vein thrombosis, remain a significant global health burden, with traditional diagnostic methods often failing to capture the complex, patient-specific nuances of thrombosis risk. This Perspective explores t...
Automated Electrical Detection of Proteins for Oral Squamous Cell Carcinoma in an Integrated Microfluidic Chip Using Multi-Frequency Impedance Cytometry and Machine Learning.
Sensors (Basel, Switzerland)
Mar 4, 2025
Proteins can act as suitable biomarkers for the prognosis and diagnosis of certain conditions and can help us gain an understanding of the fundamental processes that occur inside an organism. In this work, we present a fully automated machine learnin...
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