AIMC Topic: Point-of-Care Testing
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Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections.
Kidney international
Mar 17, 2017
The immune system has evolved to sense invading pathogens, control infection, and restore tissue integrity. Despite symptomatic variability in patients, unequivocal evidence that an individual's immune system distinguishes between different organisms...
Gram-Negative Bacterial Infections
Aged, 80 and over
Peptide Mapping
Young Adult
Peritonitis
Adult
Peritoneal Dialysis
Humans
Male
Machine Learning
Female
Biomarkers
Nonlinear Dynamics
Reproducibility of Results
Pattern Recognition, Automated
Aged
Point-of-Care Systems
Host-Pathogen Interactions
Time Factors
Area Under Curve
Middle Aged
Gram-Positive Bacterial Infections
ROC Curve
Acute Disease
Case-Control Studies
Bacteria
Adolescent
Point-of-Care Testing
Predictive Value of Tests
Smartphone-Powered Automated Image Recognition Tool for Multianalyte Rapid Tests: Application to Infectious Diseases.
Analytical chemistry
Jul 1, 2025
Point-of-Care Testing (POCT) is rapidly increasing, providing quick, user-friendly, and portable diagnostic tools. Lateral flow assays (LFAs) have been central to POCT, administering fast and cost-effective diagnosis. However, traditional LFAs are li...
Accurate Diagnosis of Colorectal Cancer Using a Combination of Lectin-Induced Recombinase Polymerase Amplification and CRISPR/Cas12a Assay on a Point-of-Care Testing Platform with Deep Learning Assistant.
Analytical chemistry
Jul 1, 2025
Specific glycosylation patterns on exosome surfaces represent novel diagnostic biomarkers for cancer liquid biopsy. Lectins can induce exosome aggregation through multiple bindings with exosomal glycoproteins. In this work, we developed a one-pot lec...
Artificial intelligence (AI) in point-of-care testing.
Clinica chimica acta; international journal of clinical chemistry
Jun 15, 2025
The integration of artificial intelligence (AI) into point-of-care testing (POCT) represents a transformative leap in modern healthcare, addressing critical challenges in diagnostic accuracy, workflow efficiency, and equitable access. While POCT has ...
Artificial intelligence enhanced microfluidic system for multiplexed point-of-care-testing of biological thiols.
Talanta
May 15, 2025
Cysteamine (CA) serves as a cystine-depleting agent employed in the management of cystinosis and a range of other medical conditions. Monitoring blood CA levels at the point of care is imperative due to the risk of toxicity associated with elevated C...
Point-of-Care Testing: The Convergence of Innovation and Accessibility in Diagnostics.
Analytical chemistry
May 13, 2025
Over the years, the evolution of point-of-care testing (POCT) has been driven by technological advancements in materials, design, and artificial intelligence, as well as breakthrough developments in wearable technologies. These innovations are shifti...
AI in Point-of-Care - A Sustainable Healthcare Revolution at the Edge.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2025
This paper examines the integration of artificial intelligence (AI) in point-of-care testing (POCT) to enhance diagnostic speed, accuracy, and accessibility, particularly in underserved regions. AI-driven POCT is shown to optimize clinical decision-m...
Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.
Archives of pathology & laboratory medicine
Mar 1, 2021
CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive ability of urine output (UOP) and creatinine contribute to the delayed recognition of AKI.
Detection of Falsely Elevated Point-of-Care Potassium Results Due to Hemolysis Using Predictive Analytics.
American journal of clinical pathology
Jul 7, 2020
OBJECTIVES: Preanalytical factors, such as hemolysis, affect many components of a test panel. Machine learning can be used to recognize these patterns, alerting clinicians and laboratories to potentially erroneous results. In particular, machine lear...
The end of Laboratory Medicine as we know it?
Clinical chemistry and laboratory medicine
Feb 25, 2019
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