We designed and implemented a novel automated negative non-invasive prenatal test (NIPT) result disclosure process using a proprietary, HIPAA-compliant web-based portal. High-risk pregnant patients who opted for NIPT from 04/2017 to 12/2018 were given the option to receive their negative result through the automated process. Patients were required to watch a brief educational video and answer evaluative questions before downloading their result. After completing the process, patients completed a survey regarding their opinion of the efficiency and convenience of the process and their satisfaction. A total of 10,170 women registered online during the study period, and 8,965 completed the automated process (88%). Out of 8,965 women, 2,121 women responded to the survey (24%). Most (2,030 of 2,101) strongly agreed/agreed that they could easily navigate the patient portal (97%); 1,852 of 1,966 strongly agreed/agreed that disclosure was efficient and convenient (94%); 1,852 of 1,960 strongly agreed/agreed that they felt informed after watching a short educational video (94%); and 1,903 of 1,967 strongly agreed/agreed that they preferred downloading results rather than waiting for their next doctor's appointment (97%). This study demonstrates high patient satisfaction with this automated and scalable solution in a high-volume health system. As the utilization of genetic testing increases, we predict greater need for innovative healthcare delivery models.
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http://dx.doi.org/10.1002/jgc4.1127 | DOI Listing |
PLoS One
January 2025
Department of Hematology and Blood Banking, Faculty of Allied Medicine, Iran University of Medical Science, Tehran, Iran.
Background: The challenges associated with traditional drug screening, such as high costs and long screening times, have led to an increase in the use of single-cell isolation technologies. Small sample volumes are required for high-throughput, cell-based assays to reduce assay costs and enable rapid sample processing. Using microfluidic chips, single-cell analysis can be conducted more effectively, requiring fewer reagents and maintaining biocompatibility.
View Article and Find Full Text PDFPLoS One
January 2025
Division of Biological Sciences, US Fish and Wildlife Southwest Regional Office, Albuquerque, New Mexico, United States of America.
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers' observations and selecting the mode classification.
View Article and Find Full Text PDFGenetics
January 2025
EMBL-EBI - Non-Vertebrate Genomics Team, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK.
The rapid increase in the number of reference-quality genome assemblies presents significant new opportunities for genomic research. However, the absence of standardized naming conventions for genome assemblies and annotations across datasets creates substantial challenges. Inconsistent naming hinders the identification of correct assemblies, complicates the integration of bioinformatics pipelines, and makes it difficult to link assemblies across multiple resources.
View Article and Find Full Text PDFJ Eval Clin Pract
February 2025
Surgical Nursing Department, Faculty of Health Sciences, Afyonkarahisar Health Sciences University, Afyonkarahisar, Turkey.
Aims: This study aims of determine the mediating role of individual innovativeness in the effect of nursing students' artificial intelligence anxiety on their robotic surgery knowledge level.
Design: This study was cross-sectional type.
Methods: It was conducted with 391 students.
J Neurol
January 2025
Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, Praha 6, 16000, Prague, Czech Republic.
Background And Objectives: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD.
Methods: Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing.
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