AIMC Topic: Disease

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HerGePred: Heterogeneous Network Embedding Representation for Disease Gene Prediction.

IEEE journal of biomedical and health informatics Jul 1, 2019
The discovery of disease-causing genes is a critical step towards understanding the nature of a disease and determining a possible cure for it. In recent years, many computational methods to identify disease genes have been proposed. However, making ...
Humans Machine Learning Databases, Genetic Models, Statistical Disease Algorithms Computational Biology
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Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.

Journal of the American Medical Informatics Association : JAMIA Feb 1, 2019
Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology Gamuts Ontology (RGO)-an ontology of 16 918 diseases, interventions, and imaging observations-provides a resource for differential diagnosis and auto...
Systems Integration Biological Ontologies Disease Humans Phenotype Diagnosis, Differential Radiography
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Human Disease Ontology 2018 update: classification, content and workflow expansion.

Nucleic acids research Jan 8, 2019
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...
Biological Ontologies Disease Databases, Factual Workflow Humans
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PreMedKB: an integrated precision medicine knowledgebase for interpreting relationships between diseases, genes, variants and drugs.

Nucleic acids research Jan 8, 2019
One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique 'omics' features of each individual patient, thus maximizing drug efficacy and minimizing adver...
Reproducibility of Results Pharmacogenetics Computational Biology Humans Precision Medicine Disease Genetic Variation Information Storage and Retrieval Internet Knowledge Bases
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Machine learning approach to literature mining for the genetics of complex diseases.

Database : the journal of biological databases and curation Jan 1, 2019
To generate a parsimonious gene set for understanding the mechanisms underlying complex diseases, we reasoned it was necessary to combine the curation of public literature, review of experimental databases and interpolation of pathway-associated gene...
Databases, Genetic Area Under Curve Disease Data Mining ROC Curve Models, Theoretical Humans Machine Learning
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Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2018
OBJECTIVE: To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoin...
Prognosis Data Anonymization Deep Learning Electronic Health Records Humans Disease Neural Networks, Computer
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piMGM: incorporating multi-source priors in mixed graphical models for learning disease networks.

Bioinformatics (Oxford, England) Sep 1, 2018
MOTIVATION: Learning probabilistic graphs over mixed data is an important way to combine gene expression and clinical disease data. Leveraging the existing, yet imperfect, information in pathway databases for mixed graphical model (MGM) learning is a...
Humans Software Reproducibility of Results Disease Databases, Factual Machine Learning Sample Size
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Rodents move towards the Disease Ontology.

Lab animal Jun 1, 2018
Rodentia Disease Gene Ontology Rats Animals Databases, Genetic Mice
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Opportunities and obstacles for deep learning in biology and medicine.

Journal of the Royal Society, Interface Apr 1, 2018
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine ar...
Deep Learning Decision Making Biomedical Research Disease Humans Drug Design Terminology as Topic Algorithms Delivery of Health Care Electronic Health Records Biomedical Technology
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Machine Learning Methods in Precision Medicine Targeting Epigenetic Diseases.

Current pharmaceutical design Jan 1, 2018
BACKGROUND: On a tide of big data, machine learning is coming to its day. Referring to huge amounts of epigenetic data coming from biological experiments and clinic, machine learning can help in detecting epigenetic features in genome, finding correl...
Disease Precision Medicine Epigenomics Humans Machine Learning
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