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Rapid and automated interpretation of CRISPR-Cas13-based lateral flow assay test results using machine learning.
Sens Diagn
December 2024
Department of Bioengineering, Rice University Houston TX 77030 USA
CRISPR-Cas-based lateral flow assays (LFAs) have emerged as a promising diagnostic tool for ultrasensitive detection of nucleic acids, offering improved speed, simplicity and cost-effectiveness compared to polymerase chain reaction (PCR)-based assays. However, visual interpretation of CRISPR-Cas-based LFA test results is prone to human error, potentially leading to false-positive or false-negative outcomes when analyzing test/control lines. To address this limitation, we have developed two neural network models: one based on a fully convolutional neural network and the other on a lightweight mobile-optimized neural network for automated interpretation of CRISPR-Cas-based LFA test results.
View Article and Find Full Text PDFAutomated analysis for glaucoma screening of retinal videos acquired with smartphone-based ophthalmoscope.
Heliyon
July 2024
D-Eye Srl, Padova, 35131, Italy.
Widespread screening is crucial for the early diagnosis and treatment of glaucoma, the leading cause of visual impairment and blindness. The development of portable technologies, such as smartphone-based ophthalmoscopes, able to image the optical nerve head, represents a resource for large-scale glaucoma screening. Indeed, they consist of an optical device attached to a common smartphone, making the overall device cheap and easy to use.
View Article and Find Full Text PDFSmart luminescent materials have drawn a significant attention owing to their unique optical properties and versatility in sensor applications. These materials, encompassing a broad spectrum of organic, inorganic, and hybrid systems including quantum dots, organic dyes, and metal-organic frameworks (MOFs), offer tunable emission characteristics that can be engineered at the molecular or nanoscale level to respond to specific stimuli, such as temperature, pH, and chemical presence. Recent advancements have been driven by the integration of nanotechnology, which enhances the sensitivity and selectivity of luminescent materials in sensor platforms.
View Article and Find Full Text PDFAccuracy (trueness and precision) of 3-dimensional virtual patients: an in vitro investigation of different facial scanners and digital integration techniques.
J Dent
January 2025
Department of Biologic and Materials Sciences & Prosthodontics, University of Michigan School of Dentistry, Ann Arbor, MI, USA. Electronic address:
Objectives: To investigate the influence of different facial scanners and integration approaches on the accuracy of virtual dental patients (VDPs).
Methods: Forty VDPs were generated using a head mannequin and two facial scanners: 1) an industrial scanner and 2) a smartphone scanner. For each scanner, two integration methods were applied: 1) integration by virtual facebow scan and 2) integration by nose-teeth scan.
Enhanced detection of atrial fibrillation in single-lead electrocardiograms using a cloud-based artificial intelligence platform.
Heart Rhythm
January 2025
IDOVEN Research, Madrid, Spain; Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain; Centro de Investigación Biomédica en Red. Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain. Electronic address:
Background: Although smartphone-based devices have been developed to record 1-lead ECG, existing solutions for automatic atrial fibrillation (AF) detection often has poor positive predictive value.
Objective: This study aimed to validate a cloud-based deep learning platform for automatic AF detection in a large cohort of patients using 1-lead ECG records.
Methods: We analyzed 8,528 patients with 30-second ECG records from a single-lead handheld ECG device.
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