Publications by authors named "J A Fuhrman"
Multi-institutional development and testing of attention-enhanced deep learning segmentation of thyroid nodules on ultrasound.
Int J Comput Assist Radiol Surg
January 2025
Purpose: Thyroid nodules are common, and ultrasound-based risk stratification using ACR's TIRADS classification is a key step in predicting nodule pathology. Determining thyroid nodule contours is necessary for the calculation of TIRADS scores and can also be used in the development of machine learning nodule diagnosis systems. This paper presents the development, validation, and multi-institutional independent testing of a machine learning system for the automatic segmentation of thyroid nodules on ultrasound.
View Article and Find Full Text PDFBackground: Plant-based diets are associated with lower inflammatory biomarkers and reduced risk of age-related chronic diseases. Epigenetic biomarkers of aging are DNA methylation-based tools that estimate biological age and rate of aging, providing insights into age-related health risks. Healthy diet and lifestyle indicators correlate with slower epigenetic aging.
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- - The study evaluates the effectiveness of a new AI system, MOM-ClaSeg, in helping radiologists detect lung abnormalities from chest X-ray images more accurately and efficiently.
- - Over 36,000 chest X-rays were analyzed, comparing traditional double readings by two radiologists with a single reading enhanced by AI, showing notable improvements in diagnostic accuracy and speed with AI assistance.
- - Results indicate that using AI as the first reader significantly boosts diagnostic accuracy by 1.49% and sensitivity by 10.95%, while also cutting average reading time by about 54.70%.
Article Synopsis
- Marine microbial ecologists aim to measure organismal abundance and diversity in ecosystems at a high taxonomic resolution, using various methods to capture accurate data.
- Traditional flow cytometry estimates the number of microbial cells but lacks the ability to differentiate among many species, while amplicon sequencing offers detailed taxonomic data but often only provides relative abundances.
- This study introduces a technique that combines genomic internal standards with amplicon sequencing, allowing for accurate absolute cell counts of marine picocyanobacteria, which aligns closely with flow cytometry results, indicating a reliable method for analyzing microbial populations in complex marine environments.
Nucleocytoplasmic Large DNA Viruses (NCLDVs, also called giant viruses) are widespread in marine systems and infect a broad range of microbial eukaryotes (protists). Recent biogeographic work has provided global snapshots of NCLDV diversity and community composition across the world's oceans, yet little information exists about the guiding 'rules' underpinning their community dynamics over time. We leveraged a five-year monthly metagenomic time-series to quantify the community composition of NCLDVs off the coast of Southern California and characterize these populations' temporal dynamics.
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