The present revision describes the ontologies and its use in the computer reasoning to meet the precise classification of patients for diagnosis, the administration of the assistance and the translational investigation
Introduction
The classification of patients allowed for precision medicine increases the diagnostic and medical treatment. The availability of clinical data and scientific information available allows the creation of classification strategies that relate to the intervention mechanisms of patient subgroups.
The use of the ontologies (systematic representations of knowledge) to interpret and analyze large amounts of heterogeneous data allowing to classify a patient in a precise manner.
The present revision describes the ontologies and its use in the computer reasoning to meet the precise classification of patients for diagnosis, the administration of the assistance and the translational investigation.
The abundance of dates
The electronic health records (RSE) can be used to retrieve subjective and objective observations related to demographic characteristics, hallucinations, symptoms, diagnostics, medications, among others.
The results of genomic, proteomic and metabolic analyzes are currently used in clinical analysis. Additionally, public data can be used as a reference to compare clinical data. The quantity and quality of the accumulated data have no precedents in human history.
Frequently the phenotypic information about individual patients is incomplete or inaccessible and impedes the detection of similarities and the classification of patients within clinical utility groups.
Credits, this detection and classification is seriously challenging and important, but the main objective of the precision medicine is to use these data to stratify the patients and detect similarities between the separated distances.
From sent to dates
The methods of inference needed to categorize the topics of agreement with the covariates, the characteristics or both. It is necessary to create useful classifications that conjugate a numerical plural or continuous variables, dichotomies, ordinary groups and taxonomic categories.
The classifications are called the entities in each domain and include computer specifications of different degrees of sophistication. The mechanisms for naming and specifying its relations to other of the simple terminologies and the ontologies.
The dates of the series will be the first step in making sure that the dates are computerized and the patients are classified in a profound manner. The integrated formats and structures of different sources for compatible devices are the biggest challenge.
The dates of the dates for the classification are comparable and consistent
The estates of the dates can be reduced in structure and semantics. The structure takes into account the availability of the data, it can be in a slipper or a data base scheme. Semantics refers to the concepts and relationships between them.
The software systems require assertions about the equivalence of the terms, and the mapping of clinical data traces of the systems or the data of the basic science is compromised by the differences in the number systems or the structure.
La semantics and structure has a straightforward relationship, the storage of information sources must accommodate different semantic foundations and anticipate the modifications of the semantics of harmony with its local context. Can align data to patients’ pathways and systems with comparable and consistent formats and meaningful contextual series fundamental to precision medicine.
From terminology to ontology
The terminologies used are timely in the retrieval of information from various sources. These sources, which include standardized numbers and lists of synonyms and references, are proportionate to the base for search and indexing and are frequently used in RSE and public data bases.
Burden ontologies define the relationships between the concepts, which allow the logical logic of computing.
An ontology is a set of concepts and synonyms, as well as the definitions of the logical description that specifies the formal relations between the concepts.
The use of descriptive logics in an ontology guarantees logical consistency which allows the computational reasoning procedures identified which are implied by the manner in which they are expressed in the original data.
The ontologies allowed to approve the latent knowledge within the large clinical data and can be used in combination with the natural language processing to develop concepts of the texts.
In addition, the ontologies can support the integration of basic science data and public knowledge, which allow the classification of patients on data that are most relevant to the new RSE and new clinical perspectives.
The ontologies for the classification of nurses
The Linnaeus classification used to remove the ontology of the sick given as a basis for the first edition of the International Classification of Diseases (ICD). This is a continuous continuation of the epidemiology, health and billing control, but not as a patient computer representation as a biological subject.
| The ICD’s biggest problem is that historical editions have statistical classifications that are mutually exclusive and exhaustive. |
The ICD each code has only one cause and excludes the multiple content and creates arbitrary associations. The mono-jérquías limitan have important characterization and research, in addition to impeding significant analysis of the disease and other phenotypes.
La classic breed de las enfermedades asocia el phenotype with the characteristics of a person whose attributes are related to the genotype and the term together with the data and medical records is used by the investigators to define a cohort of patients with the same diagnosis.
Following a study, computerize the algorithms of the phenotype and the work of the medical centers with different systems of RSE series útil. However, the codes used in these algorithms are captured with billing fines and not for differential diagnosis.
The SNOMED CT is a compositional system that can be used in different ways within systems and contexts different and by different users and to date the very significant conceptual and computational, so it will take a sale on terminology. Geen hindernis, less than a quarter of the content of SNOMED CT is defined by logical form.
The ontologies can organize and analyze large amounts of data that are difficult to manage by a physician in addition to improving the ability of it to classify patients.
The rare diseases and the ontology of the human phenotype
The sequencing of the exomes and the gene permits discover numbers of newly associated genes and the genes and, in some cases, this diagnostic modifies the clinical treatment.
The complete clinical significance of the genetic analysis based on genetic variants requires additional information on the phenotypes and phenotypic abnormalities.
The Human Phenotype Ontology (HPO) relates the computerized phenotypic profiles of human nurses and individual patients with terms that are related to another in the hierarchy and found to agree with the specificity of individual phenotypic abnormalities.
The HPO proposes a more detailed representation of the clinical phenotypes other clinical and ontological terminologies, and is designed for computer analysis. In addition, this method represents the patient as a biological subject.
The use of phenotypic experience based on the HPO combined with the hybrid genetic sequencing allowed the prioritization of gene candidates with the pathogenic variants predicted.
The future of ontologies in medicine
One can use the large amount of data available to classify patients and identify effective and safe treatments.
A forum will propose a new taxonomy for biology and structured medicine to reconstruct and approve the multiple sciences of basic science and clinical features such as a matrix that defines the endotypes of the nurses. Debe logarse that the annotation of the dates with ontological labels is an automated fund area.
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Burden methods of individualized medicine encuentran obstructive obstruction.
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