AIMC Topic: Point-of-Care Testing

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Technologies for the point-of-care diagnosis of malaria: a scoping review.

Infectious diseases of poverty
BACKGROUND: Malaria continues to pose a significant health challenge, particularly in low-resource settings (LRS), where access to reliable and timely diagnostics is often limited. In this context, point-of-care (POC) in vitro diagnostics (IVDs) play...

Single-Protein Determinations by Magnetofluorescent Qubit Imaging with Artificial-Intelligence Augmentation at the Point-Of-Care.

ACS nano
Conventional point-of-care testing (POCT) has limitations in sensitivity with high risks of missed detection or false positive, which restrains its applications for routine outpatient care analysis and early clinical diagnosis. By merits of the cutti...

Deep-Learning-Assisted Microfluidic Immunoassay via Smartphone-Based Imaging Transcoding System for On-Site and Multiplexed Biosensing.

Nano letters
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...

Machine learning in point-of-care testing: innovations, challenges, and opportunities.

Nature communications
The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (...

High-throughput point-of-care serum iron testing utilizing machine learning-assisted deep eutectic solvent fluorescence detection platform.

Journal of colloid and interface science
In this study, a high-throughput point-of-care testing (HT-POCT) system for detecting serum iron was developed using a hydrophobic deep eutectic solvent (HDES) fluorescence detection platform. This machine learning-assisted portable platform enables ...

Integrated Ultrasound-Enrichment and Machine Learning in Colorimetric Lateral Flow Assay for Accurate and Sensitive Clinical Alzheimer's Biomarker Diagnosis.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The colloidal gold nanoparticle (AuNP)-based colorimetric lateral flow assay (LFA) is one of the most promising analytical tools for point-of-care disease diagnosis. However, the low sensitivity and insufficient accuracy still limit its clinical appl...

Advancing Point-of-Care Testing by Application of Machine Learning Techniques and Artificial Intelligence.

Chest
The promise of artificial intelligence has generated enthusiasm among patients, health care professionals, and technology developers who seek to leverage its potential to enhance the diagnosis and management of an increasing number of chronic and acu...

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 ...

Rapid deep learning-assisted predictive diagnostics for point-of-care testing.

Nature communications
Prominent techniques such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and rapid kits are currently being explored to both enhance sensitivity and reduce assay time for diagnostic tests. Existing commerc...

Non-Contact Thermal and Acoustic Sensors with Embedded Artificial Intelligence for Point-of-Care Diagnostics.

Sensors (Basel, Switzerland)
This work involves exploring non-invasive sensor technologies for data collection and preprocessing, specifically focusing on novel thermal calibration methods and assessing low-cost infrared radiation sensors for facial temperature analysis. Additio...