AIMC Topic: Biosensing Techniques

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Machine Learning-Assisted Fe-N-C Single-Atom Nanozyme Rapid Screening Platform for Acetylcholinesterase Inhibitors.

Analytical chemistry
Traditional screening methods for acetylcholinesterase inhibitors (AChEIs) encounter significant challenges due to two primary factors: subjective errors in colorimetric analysis and reliance on laboratory instruments. To overcome these limitations, ...

Hydrogel-based sensors for multimodal health monitoring: from material design to intelligent sensing.

Nanoscale
Hydrogels, due to their biocompatibility, tunability, and stimulus responsiveness, are promising materials for flexible health monitoring. However, traditional hydrogel sensors suffer from various limitations in terms of long-term stability, signal f...

Fuel-Free Rolosense: Viral Sensing Using Diffusional Particle Tracking.

ACS sensors
High-sensitivity viral diagnostics typically use PCR to detect and amplify viral nucleic acids which requires fluorescence reporters, enzymatic amplification, specialized equipment and can be time-consuming. In this work, we describe fuel-free (FF) R...

Silver-Programmed Dual-Optical Au Nanostructures and Machine Learning for Intelligent Biosensing.

Analytical chemistry
The evolution of biosensors demands synergistic improvements in signal transduction and data processing. We present a universal biosensing platform that combines dual-mode signal responses from silver-modulated gold nanorods (AuNRs) and gold-silver n...

Smartphone-based biosensing: a review of optical imaging, microfluidic integration, and AI-enhanced analysis.

Mikrochimica acta
Recently, the integration of smartphone-based platforms into biomedical sensing has provided portable, low-cost, and scalable alternatives to conventional laboratory diagnostics. According to the advances in mobile imaging, embedded sensors, microflu...

Polymer-Functionalized Carbon Nanotube Sensors for Volatile Organic Compound Signal Exchange and Bioinspired Molecular Communication.

ACS sensors
Conventional electromagnetic communication systems face limitations in dense environments, including high energy consumption, signal attenuation, and interference. To overcome these challenges, we present a bioinspired molecular communication (MC) pl...

Artificial Intelligence for Noninvasive Health Diagnostics.

ACS sensors
Noninvasive diagnostic approaches are essential for early detection, patient compliance, and reduction of healthcare burden, yet they often face limitations in sensitivity, specificity, and timely interpretation. Artificial intelligence (AI) and mach...

Tracing the evolution in sleep apnea detection: a review from traditional non-contact under-the-mattress devices to advanced AI-driven methods.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: Sleep apnea is traditionally diagnosed with polysomnography (PSG), which, while effective, is costly, time-consuming, and obtrusive. Recent advancements in biosensing technologies have facilitated the development of under-the-mattress dev...

Personalized Cancer-Specific Protein-Aptamer Corona for Orthogonal Multiplex Cancer Diagnosis.

Journal of the American Chemical Society
Aptamers are powerful synthetic recognition elements for biosensing, yet their application in complex biofluids, such as human serum, is critically limited by enzymatic degradation. To overcome this fundamental challenge, we introduce a novel analyti...

Advancement of machine learning algorithms in biosensors.

Clinica chimica acta; international journal of clinical chemistry
Biosensors have emerged as transformative tools in modern diagnostics, enabling rapid, accurate, and sensitive detection of biological markers for disease diagnosis, real-time monitoring, and personalized healthcare. However, current biosensors still...