Publications by authors named "J J Finer"
Article Synopsis
- A novel deep learning (DL) system was developed to enhance the interpretation of transthoracic echocardiography (TTE) for assessing the severity of mitral regurgitation (MR) by integrating multiple video assessments.
- The system was tested with a large dataset (over 61,000 TTEs) and showed high accuracy in classifying MR severity, achieving exact accuracy rates of 82% for internal and 79% for external test sets.
- Most misclassifications occurred between none/trace and mild MR categories, and the use of multiple TTE views improved classification accuracy.
We characterize GFP expression driven by a soybean glycinin promoter in transgenic soybean. We demonstrate specific amino acid-mediated induction of this promoter in developing soybean seeds in vitro. In plants, gene expression is primarily regulated by promoter regions which are located upstream of gene coding sequences.
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- Valvular heart disease, specifically aortic stenosis (AS), aortic regurgitation (AR), and mitral regurgitation (MR), is a significant but often underdiagnosed issue that deep learning analysis of electrocardiograms (ECGs) can potentially address.
- The study involved 77,163 patients and developed deep learning algorithms to accurately identify moderate to severe cases of AS, AR, and MR using ECG data, achieving good performance metrics, especially for AS (AU-ROC: 0.88).
- Results suggest that deep learning could be integrated into screening programs for valvular heart disease, showing high sensitivity and specificity, particularly at low disease prevalence rates.
Successful regeneration of genetically modified plants from cell culture is highly dependent on the species, genotype, and tissue-type being targeted for transformation. Studies in some plant species have shown that when expression is altered, some genes regulating developmental processes are capable of triggering plant regeneration in a variety of plant cells and tissue-types previously identified as being recalcitrant to regeneration. In the present research, we report that developmental genes encoding GROWTH-REGULATING FACTORS positively enhance regeneration and transformation in both monocot and dicot species.
View Article and Find Full Text PDFSoybean expressing small interfering RNA of SCN improved plant resistance to SCN consistently, and small RNA-seq analysis revealed a threshold of siRNA expression required for resistance ability. Soybean cyst nematode (SCN), Heterodera glycines, is one of the most destructive pests limiting soybean production worldwide, with estimated losses of $1 billion dollars annually in the USA alone. RNA interference (RNAi) has become a powerful tool for silencing gene expression.
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