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Published in 2024 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaf209
Abstract: Abstract Summary In this paper, we introduce the first diffusion model designed to generate complete synthetic human genotypes, which, by standard protocols, one can straightforwardly expand into full-length, DNA-level genomes. The synthetic genotypes mimic real…
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Keywords:
synthetic genotypes;
genotypes using;
generating synthetic;
using diffusion ... See more keywords
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Published in 2021 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2021.3051806
Abstract: Deep learning can bring time savings and increased reproducibility to medical image analysis. However, acquiring training data is challenging due to the time-intensive nature of labeling and high inter-observer variability in annotations. Rather than labeling…
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Keywords:
labeled data;
generating synthetic;
synthetic labeled;
data existing ... See more keywords
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Published in 2024 at "Studies in health technology and informatics"
DOI: 10.3233/shti241099
Abstract: Natural Language Processing (NLP) has shown promise in fields like radiology for converting unstructured into structured data, but acquiring suitable datasets poses several challenges, including privacy concerns. Specifically, we aim to utilize Large Language Models…
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Keywords:
large language;
emergency;
language;
generating synthetic ... See more keywords
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Published in 2025 at "Applied Sciences"
DOI: 10.3390/app151910636
Abstract: Synthetic data has emerged as a significant alternative to more costly and time-consuming data collection methods. This assertion is particularly salient in the context of training facial expression recognition (FER) and generation models. The EmoStyle…
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Keywords:
facial expression;
space;
facial expressions;
generating synthetic ... See more keywords