AIMC Topic: Rare Diseases

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Incorporating Knowledge-Driven Insights into a Collaborative Filtering Model to Facilitate the Differential Diagnosis of Rare Diseases.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Rare diseases, although individually rare, collectively affect one in ten Americans. Because of their rarity, patients with rare diseases are typically left misdiagnosed or undiagnosed, which leads to a prolonged medical journey. The diagnosis pathwa...
Statistics as Topic Rare Diseases Knowledge Discovery Humans Algorithms Diagnosis, Differential Systematized Nomenclature of Medicine Biological Ontologies Knowledge Bases Data Collection
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Deep neural models for extracting entities and relationships in the new RDD corpus relating disabilities and rare diseases.

Computer methods and programs in biomedicine Jul 20, 2018
BACKGROUND AND OBJECTIVE: There is a huge amount of rare diseases, many of which have associated important disabilities. It is paramount to know in advance the evolution of the disease in order to limit and prevent the appearance of disabilities and ...
Natural Language Processing Neural Networks, Computer Rare Diseases Databases, Factual Data Mining Semantics Deep Learning Persons with Disabilities Humans
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Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning.

Scientific reports Jul 13, 2018
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of p...
ROC Curve Data Interpretation, Statistical Models, Biological Supervised Machine Learning Young Adult Databases, Factual Adult Female Male Narcolepsy Datasets as Topic Polysomnography Humans Stochastic Processes Sleep, REM Rare Diseases Sleep Latency
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Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers.

Artificial intelligence in medicine May 10, 2018
OBJECTIVE: Death certificates are an invaluable source of cancer mortality statistics. However, this value can only be realised if accurate, quantitative data can be extracted from certificates-an aim hampered by both the volume and variable quality ...
Humans Databases, Factual Reproducibility of Results Neoplasms Registries Data Mining Data Accuracy Rare Diseases Support Vector Machine Natural Language Processing Cause of Death New South Wales Death Certificates
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Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. Patients with rare diseases are frequently misdiagnosed or undiagnosed which may due to the lack of knowledge and experience of care providers. We...
Humans Algorithms Phenotype Natural Language Processing Semantics Electronic Health Records Cohort Studies Unified Medical Language System Symptom Assessment Rare Diseases
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Sensitive detection of rare disease-associated cell subsets via representation learning.

Nature communications Apr 6, 2017
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to de...
Neoplasm, Residual Single-Cell Analysis Leukemia Monocytes Immunologic Memory Humans Signal Transduction Supervised Machine Learning Killer Cells, Natural Cytokines Neural Networks, Computer Acquired Immunodeficiency Syndrome Survival Analysis Prognosis T-Lymphocyte Subsets Cytomegalovirus Infections Rare Diseases
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The Human Phenotype Ontology in 2017.

Nucleic acids research Nov 28, 2016
Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.hum...
Translational Research, Biomedical Biological Ontologies Rare Diseases Genomics Genetic Association Studies Computational Biology Software Algorithms Phenotype Precision Medicine Humans
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Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation.

Journal of biomedical semantics Mar 23, 2016
BACKGROUND: The Centre for Therapeutic Target Validation (CTTV - https://www.targetvalidation.org/) was established to generate therapeutic target evidence from genome-scale experiments and analyses. CTTV aims to support the validity of therapeutic t...
Inflammatory Bowel Diseases Reproducibility of Results Data Mining Biological Ontologies Molecular Targeted Therapy Humans Rare Diseases Phenotype Databases, Factual
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Integrating ontologies of rare diseases and radiological diagnosis.

Journal of the American Medical Informatics Association : JAMIA Mar 31, 2015
PURPOSE: The author sought to integrate an ontology of rare diseases with a large ontological model of radiological diagnosis.
Biological Ontologies Humans Radiology Rare Diseases Radiography Databases as Topic
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Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.

Nucleic acids research Oct 27, 2014
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens ...
Genetic Diseases, Inborn Biological Ontologies Humans Disease Databases, Factual Rare Diseases Internet
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