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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242502 | PMC |
| http://dx.doi.org/10.1111/ped.14582 | DOI Listing |
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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 PDFAggregating multiple test results to improve medical decision-making.
PLoS Comput Biol
January 2025
Department of Computational Medicine, University of California, Los Angeles, Los Angeles, California, United States of America.
Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive) and type II (false negative) errors. In this work, we develop a statistical model to study how medical decision-making can be improved by aggregating results from repeated diagnostic and screening tests. Our approach is relevant to not only clinical settings such as medical imaging, but also to public health, as highlighted by the need for rapid, cost-effective testing methods during the SARS-CoV-2 pandemic.
View Article and Find Full Text PDFUnlocking the potential of miRNAs in detecting pulmonary tuberculosis: prospects and pitfalls.
Expert Rev Mol Med
December 2024
Department of Internal Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, USA.
Tuberculosis (TB) is one of the deadliest infectious diseases globally, ranking as 13th leading cause of mortality and morbidity. According to the Global Tuberculosis Report 2022, TB claimed the lives of 1.6 million people worldwide in 2021.
View Article and Find Full Text PDFRevealr-Based Diagnostic Panel for Rapid Detection of Acute Respiratory Infections.
ACS Synth Biol
December 2024
Department of Pharmaceutical Sciences, University of California, Irvine, California 92697-3958, United States.
RNA-encoded viral nucleic acid analyte reporter (REVEALR) is a rapid and highly sensitive point-of-care diagnostic developed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection, genotyping, and quantification. Here, we extend the breadth of this nucleic acid technology to include a viral respiratory panel that can detect low attomolar levels of influenza A (IAV), influenza B (IBV), SARS-CoV-2 (CoV2), and the respiratory syncytial virus (RSV). Of 39 clinical samples collected at the UCI Medical Center in Orange, California, the extended REVEALR panel showed a positive predictive agreement and negative predictive agreement of 100% for IAV, CoV2, and RSV in sequence-verified clinical samples, with 0 false positive results.
View Article and Find Full Text PDFUtility of post-admission SARS-CoV-2 serial testing in hospitalized patients with cancer.
Infect Control Hosp Epidemiol
December 2024
Infection Control, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Background: SARS-CoV-2 asymptomatic surveillance testing (AST) is a common strategy to minimize the risk of nosocomial infection in patients and healthcare personnel. In contrast to admission screening, post-admission AST was less widely adopted.
Objective: This study describes the diagnostic yield of post-admission serial SARS-COV-2 testing in hospitalized patients at a large cancer center with mostly double-occupancy rooms.
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