AIMC Topic: Disease

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Similar Disease Prediction With Heterogeneous Disease Information Networks.

IEEE transactions on nanobioscience Jul 1, 2020
Studying the similarity of diseases can help us to explore the pathological characteristics of complex diseases, and help provide reliable reference information for inferring the relationship between new diseases and known diseases, so as to develop ...
Machine Learning Algorithms Humans Models, Statistical Semantics Disease Databases, Factual Computational Biology
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[Prognostic model of small sample critical diseases based on transfer learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2020
Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was p...
Disease Humans Machine Learning Prognosis Models, Theoretical Algorithms
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mAML: an automated machine learning pipeline with a microbiome repository for human disease classification.

Database : the journal of biological databases and curation Jan 1, 2020
Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems aiming to get rid of the tediousness in manually performing ML tasks are in great demand. Here we d...
Humans Machine Learning Software Gastrointestinal Microbiome Disease Databases, Factual Computational Biology
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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 ...
Computational Biology Databases, Genetic Machine Learning Algorithms Models, Statistical Disease Humans
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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...
Radiography Biological Ontologies Systems Integration Disease Phenotype Diagnosis, Differential Humans
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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...
Humans Databases, Factual Biological Ontologies Disease Workflow
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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...
Disease Computational Biology Internet Genetic Variation Information Storage and Retrieval Knowledge Bases Humans Reproducibility of Results Precision Medicine Pharmacogenetics
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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...
Data Mining Disease Databases, Genetic Area Under Curve Machine Learning ROC Curve Models, Theoretical Humans
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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...
Deep Learning Humans Data Anonymization Disease Neural Networks, Computer Prognosis Electronic Health Records
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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...
Reproducibility of Results Software Sample Size Disease Humans Databases, Factual Machine Learning
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