AIMC Topic: Datasets as Topic

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Researching public health datasets in the era of deep learning: a systematic literature review.

Health informatics journal Jan 1, 2025
Explore deep learning applications in predictive analytics for public health data, identify challenges and trends, and then understand the current landscape. A systematic literature review was conducted in June 2023 to search articles on public hea...
Datasets as Topic Public Health Humans Deep Learning
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FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.

Current medical imaging Jan 1, 2025
BACKGROUND: Pneumonia is an acute respiratory infection that has emerged as the predominant catalyst for escalating mortality rates worldwide. In the pursuit of the prevention and prediction of pneumonia, this work employs the development of an advan...
Humans Pneumonia Datasets as Topic Federated Learning Diagnosis, Computer-Assisted Deep Learning
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KPRR: a novel machine learning approach for effectively capturing nonadditive effects in genomic prediction.

Briefings in bioinformatics Nov 22, 2024
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this...
Genome Machine Learning Epistasis, Genetic Animals Data Accuracy Models, Genetic Datasets as Topic Oryza
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Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development-a systematic review.

The Lancet. Digital health Nov 1, 2024
During the COVID-19 pandemic, artificial intelligence (AI) models were created to address health-care resource constraints. Previous research shows that health-care datasets often have limitations, leading to biased AI technologies. This systematic r...
Humans Artificial Intelligence Datasets as Topic Pandemics COVID-19
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Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple Sclerosis.

Radiology. Artificial intelligence Nov 1, 2024
Artificial intelligence (AI) models often face performance drops after deployment to external datasets. This study evaluated the potential of a novel data augmentation framework based on generative adversarial networks (GANs) that creates synthetic p...
Multiple Sclerosis Image Interpretation, Computer-Assisted Datasets as Topic Proof of Concept Study Models, Statistical Data Interpretation, Statistical ROC Curve Artificial Intelligence Magnetic Resonance Imaging Female Male Middle Aged Humans Adult
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Foundation model-driven distributed learning for enhanced retinal age prediction.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2024
OBJECTIVES: The retinal age gap (RAG) is emerging as a potential biomarker for various diseases of the human body, yet its utility depends on machine learning models capable of accurately predicting biological retinal age from fundus images. However,...
Aged Adult Humans Machine Learning Fundus Oculi Retina Aging Middle Aged Datasets as Topic Linear Models
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Utilizing active learning strategies in machine-assisted annotation for clinical named entity recognition: a comprehensive analysis considering annotation costs and target effectiveness.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2024
OBJECTIVES: Active learning (AL) has rarely integrated diversity-based and uncertainty-based strategies into a dynamic sampling framework for clinical named entity recognition (NER). Machine-assisted annotation is becoming popular for creating gold-s...
Natural Language Processing Supervised Machine Learning Datasets as Topic Humans Electronic Health Records
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Learning meaningful representation of single-neuron morphology via large-scale pre-training.

Bioinformatics (Oxford, England) Sep 1, 2024
SUMMARY: Single-neuron morphology, the study of the structure, form, and shape of a group of specialized cells in the nervous system, is of vital importance to define the type of neurons, assess changes in neuronal development and aging and determine...
Neurons Deep Learning Humans Drosophila melanogaster Datasets as Topic Animals Cell Shape Rats
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LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction.

Journal of the American Medical Informatics Association : JAMIA Sep 1, 2024
OBJECTIVE: To investigate the demonstration in large language models (LLMs) for biomedical relation extraction. This study introduces a framework comprising three types of adaptive tuning methods to assess their impacts and effectiveness.
Datasets as Topic Natural Language Processing Data Mining
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Impact of high-quality, mixed-domain data on the performance of medical language models.

Journal of the American Medical Informatics Association : JAMIA Sep 1, 2024
OBJECTIVE: To optimize the training strategy of large language models for medical applications, focusing on creating clinically relevant systems that efficiently integrate into healthcare settings, while ensuring high standards of accuracy and reliab...
Humans Natural Language Processing Datasets as Topic
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