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Table 1 Existing ontology for DM

From: An ontology network for Diabetes Mellitus in Mexico

Cite T1DM T2DM FH PD Tt DDR SR Observations Evaluation
[7] × \(\checkmark \) × \(\checkmark \) × \(\checkmark \) × This system starts from variables to determine in a diffuse way if a patient suffers from diabetes or the risk of suffering from it. Performance comparison facing Machine Learning-based classifiers.
[8] \(\checkmark \) \(\checkmark \) × \(\checkmark \) × × \(\checkmark \) This ontology proposes the degree of suffering from different types of diabetes based on specific characteristics presented at a given time in a patient. Not indicated.
[9] × \(\checkmark \) \(\checkmark \) \(\checkmark \) × \(\checkmark \) \(\checkmark \) The relation between diabetes with other diseases is only used to diagnose diabetes, not to suggest a future condition. Completeness, abstraction, cohesion, conceptualization, complexity and understanding.
[10, 11] × \(\checkmark \) \(\checkmark \) \(\checkmark \) \(\checkmark \) \(\checkmark \) \(\checkmark \) Does not include insulin-based treatments or their consequences. Validation and verification.
[12] × \(\checkmark \) × \(\checkmark \) × × \(\checkmark \) This ontology is limited to proposing a degree of propensity to suffer from diabetes and does not include any additional consequences. Consistency by Kappa Index.
[13] × \(\checkmark \) × × × \(\checkmark \) × This ontology represents knowledge associated with diabetes, limiting itself to containing only classes and relation based on the information represented in other ontologies. Validation by domain experts.
[14] × \(\checkmark \) × \(\checkmark \) × \(\checkmark \) \(\checkmark \) This ontology proposes the degree of suffering from diabetes and only includes heart conditions as a consequence of it. Functionality, reliability, efficiency, maintainability and portability.
[15] × \(\checkmark \) × \(\checkmark \) \(\checkmark \) \(\checkmark \) \(\checkmark \) This model does not provide a diagnosis of possible diseases, it only provides established information about life styles for diabetic patients. Accuracy and consistency.
[16] × \(\checkmark \) × \(\checkmark \) × \(\checkmark \) \(\checkmark \) This ontology proposes the degree of complications from values related to laboratory tests, age, and obesity degree, among others. Consistency.
[17] \(\checkmark \) \(\checkmark \) × \(\checkmark \) × × \(\checkmark \) This system is limited to working only with signs that occur in a person at a specific time, regardless of their clinical history. Cases of use.
[18] \(\checkmark \) \(\checkmark \) × \(\checkmark \) \(\checkmark \) × \(\checkmark \) This ontology has the purpose of informing about the lifestyle of a diabetic patient, discriminating the diagnosis of the disease. Scenarios and consistency.
[19] × \(\checkmark \) × × \(\checkmark \) \(\checkmark \) \(\checkmark \) This ontology represents knowledge associated with the care of diabetic patients, so it does not include any type of diagnosis. Not indicated.
[20] × \(\checkmark \) \(\checkmark \) \(\checkmark \) \(\checkmark \) × × This model is only designed to classify files based on structured information, making it impossible to give a diagnosis. Not indicated.
[21] × \(\checkmark \) × \(\checkmark \) × × \(\checkmark \) This proposal is limited to working only with clinical records, so it is incomplete as it does not have knowledge from a specialist doctor. Not indicated.
[22] × \(\checkmark \) × \(\checkmark \) \(\checkmark \) × \(\checkmark \) This ontology contains knowledge associated with diabetes, limiting itself to providing medication and food suggestions based on a patient’s condition. Recall, Precision, Accuracy and F-Measure.
  1. Abbreviations. FH Family History, PD Personal Data, Tt Treatment, DDR DM-Disease Relation, SR Semantic Rules