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Biomedical Research

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Artificial intelligence for aging and longevity research: Recent advances and perspectives.

Ageing research reviews
The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almost universal unifying feature possessed by all living organisms, tissues, and cells. Modern deep lea...

A method of inferring the relationship between Biomedical entities through correlation analysis on text.

Biomedical engineering online
BACKGROUND: One of the most important processes in a machine learning-based natural language processing is to represent words. The one-hot representation that has been commonly used has a large size of vector and assumes that the features that make u...

Introduction to Machine Learning in Digital Healthcare Epidemiology.

Infection control and hospital epidemiology
To exploit the full potential of big routine data in healthcare and to efficiently communicate and collaborate with information technology specialists and data analysts, healthcare epidemiologists should have some knowledge of large-scale analysis te...

ProvCaRe: Characterizing scientific reproducibility of biomedical research studies using semantic provenance metadata.

International journal of medical informatics
OBJECTIVE: Reproducibility of research studies is key to advancing biomedical science by building on sound results and reducing inconsistencies between published results and study data. We propose that the available data from research studies combine...

Current state and future prospects of artificial intelligence in ophthalmology: a review.

Clinical & experimental ophthalmology
Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical fields, it will have particular utility in ophthalmology and will dramatically change the diagnostic and ...

Digital diabetes: Perspectives for diabetes prevention, management and research.

Diabetes & metabolism
Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients' symptoms, physiological data, behaviours, and social and environmental ...

Linked open data-based framework for automatic biomedical ontology generation.

BMC bioinformatics
BACKGROUND: Fulfilling the vision of Semantic Web requires an accurate data model for organizing knowledge and sharing common understanding of the domain. Fitting this description, ontologies are the cornerstones of Semantic Web and can be used to so...

Extracting Biomedical Events with Parallel Multi-Pooling Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical event extraction is important for medical research and disease prevention, which has attracted much attention in recent years. Traditionally, most of the state-of-the-art systems have been based on shallow machine learning methods, which r...

SNOMED CT standard ontology based on the ontology for general medical science.

BMC medical informatics and decision making
BACKGROUND: Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic health data. Some efforts have be...