AI Medical Compendium Journal:
Journal of clinical microbiology

Showing 11 to 16 of 16 articles

Specificity of SARS-CoV-2 Real-Time PCR Improved by Deep Learning Analysis.

Journal of clinical microbiology
Real-time PCR (RT-PCR) is widely used to diagnose human pathogens. RT-PCR data are traditionally analyzed by estimating the threshold cycle ( ) at which the fluorescence signal produced by emission of a probe crosses a baseline level. Current models ...

Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist.

Journal of clinical microbiology
Artificial intelligence (AI) is increasingly becoming an important component of clinical microbiology informatics. Researchers, microbiologists, laboratorians, and diagnosticians are interested in AI-based testing because these solutions have the pot...

Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Journal of clinical microbiology
Intestinal protozoa are responsible for relatively few infections in the developed world, but the testing volume is disproportionately high. Manual light microscopy of stool remains the gold standard but can be insensitive, time-consuming, and diffic...

Machine Learning Interpretation of Extended Human Papillomavirus Genotyping by Onclarity in an Asian Cervical Cancer Screening Population.

Journal of clinical microbiology
This study aimed (i) to compare the performance of the BD Onclarity human papillomavirus (HPV) assay with the Cobas HPV test in identifying cervical intraepithelial neoplasia 2/3 or above (CIN2/3+) in an Asian screening population and (ii) to explore...

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal .

Journal of clinical microbiology
Nontyphoidal species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susceptibility data are available for strains because of surveillance efforts from public health agencie...

Automated Interpretation of Blood Culture Gram Stains by Use of a Deep Convolutional Neural Network.

Journal of clinical microbiology
Microscopic interpretation of stained smears is one of the most operator-dependent and time-intensive activities in the clinical microbiology laboratory. Here, we investigated application of an automated image acquisition and convolutional neural net...