AIMC Topic: Databases, Factual

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Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning.

Journal of digital imaging
Breast cancer is a leading cause of cancer death among women in the USA. Screening mammography is effective in reducing mortality, but has a high rate of unnecessary recalls and biopsies. While deep learning can be applied to mammography, large-scale...

An account of in silico identification tools of secreted effector proteins in bacteria and future challenges.

Briefings in bioinformatics
Bacterial pathogens secrete numerous effector proteins via six secretion systems, type I to type VI secretion systems, to adapt to new environments or to promote virulence by bacterium-host interactions. Many computational approaches have been used i...

Human Disease Ontology 2018 update: classification, content and workflow expansion.

Nucleic acids research
The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and ha...

Correlation Network Analysis Provides Important Modules and Pathways for Human Hyperlipidemia.

Critical reviews in eukaryotic gene expression
Hyperlipidemia casts great threats to humans around the world. The systemic co-expression and function enrichment analysis for this disease is limited to date. This study was to identify co-expression modules to explore hyperlipidemia-associated func...

Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.

Current medical imaging reviews
BACKGROUND: Brain tumor is the leading cause of death worldwide. It is obvious that the chances of survival can be increased if the tumor is identified and properly classified at an initial stage. MRI (Magnetic Resonance Imaging) is one source of bra...

Enabling semantic queries across federated bioinformatics databases.

Database : the journal of biological databases and curation
MOTIVATION: Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data available publicly. However, the heterogeneity of the different data sources, both at the syntactic and the ...

Evaluation of an automatic article selection method for timelier updates of the Comet Core Outcome Set database.

Database : the journal of biological databases and curation
Curated databases of scientific literature play an important role in helping researchers find relevant literature, but populating such databases is a labour intensive and time-consuming process. One such database is the freely accessible Comet Core O...

MIRKB: a myocardial infarction risk knowledge base.

Database : the journal of biological databases and curation
Myocardial infarction (MI) is a common cardiovascular disease and a leading cause of death worldwide. The etiology of MI is complicated and not completely understood. Many risk factors are reported important for the development of MI, including lifes...

FoodBase corpus: a new resource of annotated food entities.

Database : the journal of biological databases and curation
The existence of annotated text corpora is essential for the development of public health services and tools based on natural language processing (NLP) and text mining. Recently organized biomedical NLP shared tasks have provided annotated corpora re...

Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.

Journal of Alzheimer's disease : JAD
In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. This work deals with binary classification between Alzheimer's disease and cognitively normal. Supervis...